{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:56:23.537605Z",
     "iopub.status.busy": "2021-08-07T18:56:23.537091Z",
     "iopub.status.idle": "2021-08-07T18:56:23.914646Z",
     "shell.execute_reply": "2021-08-07T18:56:23.914153Z",
     "shell.execute_reply.started": "2021-08-07T18:56:23.537558Z"
    },
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   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import cv2\n",
    "import glob\n",
    "\n",
    "%pylab inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:56:26.690987Z",
     "iopub.status.busy": "2021-08-07T18:56:26.690403Z",
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     "shell.execute_reply": "2021-08-07T18:56:27.191391Z",
     "shell.execute_reply.started": "2021-08-07T18:56:26.690939Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os, sys, codecs, glob\n",
    "from PIL import Image, ImageDraw\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import cv2\n",
    "\n",
    "import torch\n",
    "torch.backends.cudnn.benchmark = False\n",
    "# torch.backends.cudnn.enabled = False\n",
    "\n",
    "import torchvision.models as models\n",
    "import torchvision.transforms as transforms\n",
    "import torchvision.datasets as datasets\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "import torch.optim as optim\n",
    "from torch.autograd import Variable\n",
    "from torch.utils.data.dataset import Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:56:27.837127Z",
     "iopub.status.busy": "2021-08-07T18:56:27.836763Z",
     "iopub.status.idle": "2021-08-07T18:56:27.842474Z",
     "shell.execute_reply": "2021-08-07T18:56:27.841783Z",
     "shell.execute_reply.started": "2021-08-07T18:56:27.837098Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "class XunFeiDataset(Dataset):\n",
    "    def __init__(self, img_path, img_group, transform):\n",
    "        self.img_path = img_path\n",
    "        self.transform = transform\n",
    "        self.group = img_group\n",
    "\n",
    "    def __getitem__(self, index):\n",
    "        img = Image.open(self.img_path[index]).convert('RGB')\n",
    "        \n",
    "        if self.transform is not None:\n",
    "            img = self.transform(img)\n",
    "        \n",
    "        return img, self.group[index]\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.img_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:56:28.796739Z",
     "iopub.status.busy": "2021-08-07T18:56:28.796232Z",
     "iopub.status.idle": "2021-08-07T18:56:28.828318Z",
     "shell.execute_reply": "2021-08-07T18:56:28.827882Z",
     "shell.execute_reply.started": "2021-08-07T18:56:28.796698Z"
    },
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   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>label</th>\n",
       "      <th>path</th>\n",
       "      <th>group</th>\n",
       "      <th>fold</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>008233.jpg</td>\n",
       "      <td>008233.jpg 006688.jpg</td>\n",
       "      <td>./电商图像检索_数据集/train/008233.jpg</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>006688.jpg</td>\n",
       "      <td>008233.jpg 006688.jpg</td>\n",
       "      <td>./电商图像检索_数据集/train/006688.jpg</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>000232.jpg</td>\n",
       "      <td>000232.jpg 003552.jpg</td>\n",
       "      <td>./电商图像检索_数据集/train/000232.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>003552.jpg</td>\n",
       "      <td>000232.jpg 003552.jpg</td>\n",
       "      <td>./电商图像检索_数据集/train/003552.jpg</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>000814.jpg</td>\n",
       "      <td>000814.jpg 013765.jpg</td>\n",
       "      <td>./电商图像检索_数据集/train/000814.jpg</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>013765.jpg</td>\n",
       "      <td>000814.jpg 013765.jpg</td>\n",
       "      <td>./电商图像检索_数据集/train/013765.jpg</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>001429.jpg</td>\n",
       "      <td>001429.jpg 014834.jpg</td>\n",
       "      <td>./电商图像检索_数据集/train/001429.jpg</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>014834.jpg</td>\n",
       "      <td>001429.jpg 014834.jpg</td>\n",
       "      <td>./电商图像检索_数据集/train/014834.jpg</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>012795.jpg</td>\n",
       "      <td>012795.jpg 015860.jpg</td>\n",
       "      <td>./电商图像检索_数据集/train/012795.jpg</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>015860.jpg</td>\n",
       "      <td>012795.jpg 015860.jpg</td>\n",
       "      <td>./电商图像检索_数据集/train/015860.jpg</td>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         name                  label                           path  group  \\\n",
       "0  008233.jpg  008233.jpg 006688.jpg  ./电商图像检索_数据集/train/008233.jpg      0   \n",
       "1  006688.jpg  008233.jpg 006688.jpg  ./电商图像检索_数据集/train/006688.jpg      0   \n",
       "2  000232.jpg  000232.jpg 003552.jpg  ./电商图像检索_数据集/train/000232.jpg      1   \n",
       "3  003552.jpg  000232.jpg 003552.jpg  ./电商图像检索_数据集/train/003552.jpg      1   \n",
       "4  000814.jpg  000814.jpg 013765.jpg  ./电商图像检索_数据集/train/000814.jpg      2   \n",
       "5  013765.jpg  000814.jpg 013765.jpg  ./电商图像检索_数据集/train/013765.jpg      2   \n",
       "6  001429.jpg  001429.jpg 014834.jpg  ./电商图像检索_数据集/train/001429.jpg      3   \n",
       "7  014834.jpg  001429.jpg 014834.jpg  ./电商图像检索_数据集/train/014834.jpg      3   \n",
       "8  012795.jpg  012795.jpg 015860.jpg  ./电商图像检索_数据集/train/012795.jpg      4   \n",
       "9  015860.jpg  012795.jpg 015860.jpg  ./电商图像检索_数据集/train/015860.jpg      4   \n",
       "\n",
       "   fold  \n",
       "0     0  \n",
       "1     0  \n",
       "2     1  \n",
       "3     1  \n",
       "4     2  \n",
       "5     2  \n",
       "6     3  \n",
       "7     3  \n",
       "8     4  \n",
       "9     4  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df = pd.read_csv('./电商图像检索_数据集/train.csv')\n",
    "train_df['path'] = './电商图像检索_数据集/train/' + train_df['name']\n",
    "\n",
    "train_df['group'] = pd.factorize(train_df['label'])[0]\n",
    "train_df['fold'] = train_df['group'] % 5\n",
    "\n",
    "train_df = train_df.sort_values(by='group')\n",
    "train_df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:56:30.082582Z",
     "iopub.status.busy": "2021-08-07T18:56:30.081997Z",
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     "shell.execute_reply.started": "2021-08-07T18:56:30.082537Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "tr_path = train_df[train_df['fold'] != 0]['path'].values\n",
    "tr_label = train_df[train_df['fold'] != 0]['group']\n",
    "tr_label = pd.factorize(tr_label)[0]\n",
    "\n",
    "val_path = train_df[train_df['fold'] == 0]['path'].values\n",
    "val_label = train_df[train_df['fold'] == 0]['group'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:56:31.516427Z",
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     "shell.execute_reply.started": "2021-08-07T18:56:31.516378Z"
    },
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "1805"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tr_label.max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:56:32.738781Z",
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     "shell.execute_reply.started": "2021-08-07T18:56:32.738733Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "train_loader = torch.utils.data.DataLoader(\n",
    "    XunFeiDataset(tr_path, tr_label,\n",
    "                        transforms.Compose([\n",
    "                        transforms.Resize((300, 300)),\n",
    "                        transforms.RandomHorizontalFlip(),\n",
    "                        transforms.RandomVerticalFlip(),\n",
    "                        transforms.ToTensor(),\n",
    "                        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
    "        ])\n",
    "    ),\n",
    "    batch_size=10, shuffle=True, num_workers=5,\n",
    ")\n",
    "\n",
    "val_loader = torch.utils.data.DataLoader(\n",
    "    XunFeiDataset(val_path, val_label,\n",
    "                        transforms.Compose([\n",
    "                        transforms.Resize((300, 300)),\n",
    "                        transforms.ToTensor(),\n",
    "                        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
    "        ])\n",
    "    ),\n",
    "    batch_size=10, shuffle=False, num_workers=5,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:56:35.261334Z",
     "iopub.status.busy": "2021-08-07T18:56:35.260760Z",
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     "shell.execute_reply.started": "2021-08-07T18:56:35.261288Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "class ArcModule(nn.Module):\n",
    "    def __init__(self, in_features, out_features, s = 10, m = 0.2):\n",
    "        super().__init__()\n",
    "        self.in_features = in_features\n",
    "        self.out_features = out_features\n",
    "        self.s = s\n",
    "        self.m = m\n",
    "        self.weight = nn.Parameter(torch.FloatTensor(out_features, in_features))\n",
    "        nn.init.xavier_normal_(self.weight)\n",
    "\n",
    "        self.cos_m = math.cos(m)\n",
    "        self.sin_m = math.sin(m)\n",
    "        self.th = torch.tensor(math.cos(math.pi - m))\n",
    "        self.mm = torch.tensor(math.sin(math.pi - m) * m)\n",
    "\n",
    "    def forward(self, inputs, labels):\n",
    "        cos_th = F.linear(inputs, F.normalize(self.weight))\n",
    "        cos_th = cos_th.clamp(-1, 1)\n",
    "        sin_th = torch.sqrt(1.0 - torch.pow(cos_th, 2))\n",
    "        cos_th_m = cos_th * self.cos_m - sin_th * self.sin_m\n",
    "        # print(type(cos_th), type(self.th), type(cos_th_m), type(self.mm))\n",
    "        cos_th_m = torch.where(cos_th > self.th, cos_th_m, cos_th - self.mm)\n",
    "        \n",
    "        cond_v = cos_th - self.th\n",
    "        cond = cond_v <= 0\n",
    "        cos_th_m[cond] = (cos_th - self.mm)[cond]\n",
    "\n",
    "        if labels.dim() == 1:\n",
    "            labels = labels.unsqueeze(-1)\n",
    "        onehot = torch.zeros(cos_th.size()).cuda()\n",
    "        labels = labels.type(torch.LongTensor).cuda()\n",
    "        onehot.scatter_(1, labels, 1.0)\n",
    "        outputs = onehot * cos_th_m + (1.0 - onehot) * cos_th\n",
    "        outputs = outputs * self.s\n",
    "        return outputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:56:36.562598Z",
     "iopub.status.busy": "2021-08-07T18:56:36.562028Z",
     "iopub.status.idle": "2021-08-07T18:56:38.643125Z",
     "shell.execute_reply": "2021-08-07T18:56:38.642232Z",
     "shell.execute_reply.started": "2021-08-07T18:56:36.562551Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import timm\n",
    "\n",
    "class XunFeiNet(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(XunFeiNet, self).__init__()\n",
    "                \n",
    "        model = model = timm.create_model('efficientnet_b2', num_classes=137, \n",
    "                          pretrained=True)\n",
    "        model.classifier = torch.nn.Identity()\n",
    "        self.model = model\n",
    "        self.margin = ArcModule(in_features=1408, \n",
    "                                out_features = 1806)\n",
    "        \n",
    "    def forward(self, img, labels=None):        \n",
    "        feat = self.model(img)\n",
    "        \n",
    "        feat = F.normalize(feat)\n",
    "        if labels is not None:\n",
    "            return self.margin(feat, labels)\n",
    "        return feat\n",
    "    \n",
    "model = XunFeiNet().cuda()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:56:38.644183Z",
     "iopub.status.busy": "2021-08-07T18:56:38.644011Z",
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     "shell.execute_reply.started": "2021-08-07T18:56:38.644168Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def train(train_loader, model, criterion, optimizer, epoch):\n",
    "    model.train()\n",
    "\n",
    "    for i, (input, target) in enumerate(train_loader):\n",
    "        input = input.cuda(non_blocking=True)\n",
    "        target = target.cuda(non_blocking=True)\n",
    "\n",
    "        output = model(input, target)\n",
    "        loss = criterion(output, target)\n",
    "\n",
    "        optimizer.zero_grad()\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        \n",
    "        if i % 40 == 0:\n",
    "            print(loss.item())\n",
    "            \n",
    "def validate(val_loader, model):\n",
    "    model.eval()\n",
    "    \n",
    "    val_feats = []\n",
    "    with torch.no_grad():\n",
    "        end = time.time()\n",
    "        for i, (input, target) in enumerate(val_loader):\n",
    "            input = input.cuda()\n",
    "            target = target.cuda()\n",
    "\n",
    "            # compute output\n",
    "            output = model(input)\n",
    "            val_feats.append(output.data.cpu().numpy())\n",
    "    return val_feats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:56:39.558129Z",
     "iopub.status.busy": "2021-08-07T18:56:39.557560Z",
     "iopub.status.idle": "2021-08-07T18:56:39.563990Z",
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     "shell.execute_reply.started": "2021-08-07T18:56:39.558083Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def set_iou(label, predict):\n",
    "    interset = set(label.split()) &  set(predict.split())\n",
    "    unionset = set(label.split()) | set(predict.split())\n",
    "    return len(interset) *1.0 / len(unionset) *1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:56:43.501084Z",
     "iopub.status.busy": "2021-08-07T18:56:43.500506Z",
     "iopub.status.idle": "2021-08-07T19:04:32.958128Z",
     "shell.execute_reply": "2021-08-07T19:04:32.956625Z",
     "shell.execute_reply.started": "2021-08-07T18:56:43.501038Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch:  0\n",
      "9.670488357543945\n",
      "9.727831840515137\n",
      "9.002659797668457\n",
      "9.433891296386719\n",
      "9.519417762756348\n",
      "9.612276077270508\n",
      "9.496158599853516\n",
      "8.945272445678711\n",
      "9.078862190246582\n",
      "9.045198440551758\n",
      "8.466023445129395\n",
      "8.43017578125\n",
      "9.007772445678711\n",
      "8.336748123168945\n",
      "Val 0.9126315789473685 0.49728474561921193\n",
      "Epoch:  1\n",
      "7.787834167480469\n",
      "8.184675216674805\n",
      "7.630574703216553\n",
      "7.9129157066345215\n",
      "8.150699615478516\n",
      "8.011946678161621\n",
      "7.4356889724731445\n",
      "7.4520087242126465\n",
      "7.824509620666504\n",
      "7.054200172424316\n",
      "6.823802947998047\n",
      "6.708046913146973\n",
      "6.767803192138672\n",
      "7.167276859283447\n",
      "Val 0.7836842105263158 0.551436823011019\n",
      "Epoch:  2\n",
      "6.667402744293213\n",
      "6.524799346923828\n",
      "6.1616411209106445\n",
      "6.7909255027771\n",
      "6.34220027923584\n",
      "6.665152072906494\n",
      "6.660321235656738\n",
      "6.004796981811523\n",
      "5.534729957580566\n",
      "6.864931583404541\n",
      "6.1565446853637695\n",
      "5.558651924133301\n",
      "6.889753818511963\n",
      "6.449324131011963\n",
      "Val 0.8094736842105263 0.5881788296302233\n",
      "Epoch:  3\n",
      "5.376856327056885\n",
      "5.12462854385376\n",
      "4.922795295715332\n",
      "5.5526933670043945\n",
      "5.057455539703369\n",
      "4.2670793533325195\n",
      "6.222679138183594\n",
      "5.359081268310547\n",
      "4.597636699676514\n",
      "5.611691951751709\n",
      "3.8793044090270996\n",
      "4.943284511566162\n",
      "5.1082000732421875\n",
      "4.561625003814697\n",
      "Val 0.7063157894736842 0.6243994090357109\n",
      "Epoch:  4\n",
      "3.8325068950653076\n",
      "3.714857816696167\n",
      "3.6709957122802734\n",
      "4.143265247344971\n",
      "4.472568035125732\n",
      "3.7847747802734375\n",
      "3.5761559009552\n",
      "3.8564915657043457\n",
      "3.8661999702453613\n",
      "3.191474437713623\n",
      "2.8481972217559814\n",
      "3.3608391284942627\n",
      "3.1112945079803467\n",
      "3.4543392658233643\n",
      "Val 0.6805263157894736 0.6389669866241426\n",
      "Epoch:  5\n",
      "2.9917094707489014\n",
      "3.1342320442199707\n",
      "2.384136438369751\n",
      "3.114887237548828\n",
      "2.532376527786255\n",
      "2.8379616737365723\n",
      "3.3800926208496094\n",
      "3.338207244873047\n",
      "2.1988606452941895\n",
      "2.4290308952331543\n",
      "3.2333972454071045\n",
      "3.0648341178894043\n",
      "2.339215040206909\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-12-c61154d03695>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      9\u001b[0m     \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Epoch: '\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mepoch\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     10\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m     \u001b[0mtrain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_loader\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcriterion\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moptimizer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mepoch\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     12\u001b[0m     \u001b[0mscheduler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-10-696f7a90b303>\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(train_loader, model, criterion, optimizer, epoch)\u001b[0m\n\u001b[1;32m     11\u001b[0m         \u001b[0moptimizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mzero_grad\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     12\u001b[0m         \u001b[0mloss\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbackward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 13\u001b[0;31m         \u001b[0moptimizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     14\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     15\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mi\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;36m40\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.6/site-packages/torch/optim/lr_scheduler.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     65\u001b[0m                 \u001b[0minstance\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_step_count\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     66\u001b[0m                 \u001b[0mwrapped\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__get__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minstance\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 67\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mwrapped\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     68\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     69\u001b[0m             \u001b[0;31m# Note that the returned function here is no longer a bound method,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.6/site-packages/torch/autograd/grad_mode.py\u001b[0m in \u001b[0;36mdecorate_context\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     24\u001b[0m         \u001b[0;32mdef\u001b[0m \u001b[0mdecorate_context\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     25\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 26\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     27\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mcast\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mF\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdecorate_context\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     28\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.6/site-packages/torch/optim/adam.py\u001b[0m in \u001b[0;36mstep\u001b[0;34m(self, closure)\u001b[0m\n\u001b[1;32m    117\u001b[0m                    \u001b[0mgroup\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'lr'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    118\u001b[0m                    \u001b[0mgroup\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'weight_decay'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 119\u001b[0;31m                    \u001b[0mgroup\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'eps'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    120\u001b[0m                    )\n\u001b[1;32m    121\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mloss\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/.local/lib/python3.6/site-packages/torch/optim/functional.py\u001b[0m in \u001b[0;36madam\u001b[0;34m(params, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, amsgrad, beta1, beta2, lr, weight_decay, eps)\u001b[0m\n\u001b[1;32m     92\u001b[0m             \u001b[0mdenom\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mmax_exp_avg_sq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msqrt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mmath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msqrt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbias_correction2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0meps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     93\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 94\u001b[0;31m             \u001b[0mdenom\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mexp_avg_sq\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msqrt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mmath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msqrt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbias_correction2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0meps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     95\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     96\u001b[0m         \u001b[0mstep_size\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlr\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mbias_correction1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "from sklearn.preprocessing import normalize\n",
    "\n",
    "criterion = nn.CrossEntropyLoss().cuda()\n",
    "optimizer = torch.optim.Adam(model.parameters(), 0.0003)\n",
    "scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=10, gamma=0.85)\n",
    "best_acc = 0.0\n",
    "\n",
    "for epoch in range(20):\n",
    "    print('Epoch: ', epoch)\n",
    "\n",
    "    train(train_loader, model, criterion, optimizer, epoch)\n",
    "    scheduler.step()\n",
    "    \n",
    "    val_feats = validate(val_loader, model)\n",
    "    val_feats = np.vstack(val_feats)\n",
    "    # val_feats = normalize(val_feats)\n",
    "    \n",
    "    val_distance = []\n",
    "    for feat in val_feats:\n",
    "        dis = np.dot(feat, val_feats.T)\n",
    "        val_distance.append(dis)\n",
    "        \n",
    "    best_threahold, best_f1 = 0, 0\n",
    "    for threahold in np.linspace(0.5, 0.99, 20):\n",
    "        val_submit = []\n",
    "        for dis in val_distance[:]:\n",
    "            pred = np.where(dis > threahold)[0]\n",
    "            if len(pred) == 1:\n",
    "                ids = dis.argsort()[::-1]\n",
    "                pred = [x for x in ids[dis[ids] > 0.1]][:2]\n",
    "\n",
    "            val_submit.append(pred)\n",
    "\n",
    "        val_f1s = []\n",
    "        for x, pred in zip(val_label, val_submit):\n",
    "            label = np.where(val_label == x)[0]\n",
    "            val_f1 = len(set(pred) & set(label)) / len(set(pred) | set(label)) \n",
    "            val_f1s.append(val_f1)\n",
    "\n",
    "        if best_f1 < np.mean(val_f1s):\n",
    "            best_f1 = np.mean(val_f1s)\n",
    "            best_threahold = threahold\n",
    "\n",
    "    print('Val', best_threahold, best_f1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:37:11.691327Z",
     "iopub.status.busy": "2021-08-07T18:37:11.690746Z",
     "iopub.status.idle": "2021-08-07T18:37:11.711212Z",
     "shell.execute_reply": "2021-08-07T18:37:11.709972Z",
     "shell.execute_reply.started": "2021-08-07T18:37:11.691279Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "test_path = glob.glob('./电商图像检索_数据集/test/*')\n",
    "test_path.sort()\n",
    "test_path = np.array(test_path)\n",
    "\n",
    "test_loader = torch.utils.data.DataLoader(\n",
    "    XunFeiDataset(test_path, [0]*len(test_path),\n",
    "                        transforms.Compose([\n",
    "                        transforms.Resize((224, 224)),\n",
    "                        transforms.ToTensor(),\n",
    "                        transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])\n",
    "        ])\n",
    "    ),\n",
    "    batch_size=50, shuffle=False, num_workers=5,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:37:12.793404Z",
     "iopub.status.busy": "2021-08-07T18:37:12.792842Z",
     "iopub.status.idle": "2021-08-07T18:37:23.938695Z",
     "shell.execute_reply": "2021-08-07T18:37:23.937818Z",
     "shell.execute_reply.started": "2021-08-07T18:37:12.793356Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "model.eval()\n",
    "test_feats = []\n",
    "with torch.no_grad():\n",
    "    for data in test_loader:\n",
    "        data = data[0].cuda()\n",
    "        feat = model(data)\n",
    "        test_feats.append(feat.data.cpu().numpy())\n",
    "        \n",
    "test_feats = np.vstack(test_feats)\n",
    "test_feats = normalize(test_feats)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:37:23.940112Z",
     "iopub.status.busy": "2021-08-07T18:37:23.939924Z",
     "iopub.status.idle": "2021-08-07T18:37:27.496296Z",
     "shell.execute_reply": "2021-08-07T18:37:27.495521Z",
     "shell.execute_reply.started": "2021-08-07T18:37:23.940094Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "test_submit = []\n",
    "for path, feat in zip(test_path[:], test_feats[:]):\n",
    "    dis = np.dot(feat, test_feats.T)\n",
    "    pred = [x.split('/')[-1] for x in test_path[np.where(dis > 0.85)[0]]]\n",
    "    if len(pred) == 1:\n",
    "        ids = dis.argsort()[::-1]\n",
    "        pred = [x.split('/')[-1] for x in test_path[ids[:2]]]\n",
    "    \n",
    "    test_submit.append([\n",
    "        path.split('/')[-1],\n",
    "        pred\n",
    "    ])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:37:27.497904Z",
     "iopub.status.busy": "2021-08-07T18:37:27.497456Z",
     "iopub.status.idle": "2021-08-07T18:37:27.517783Z",
     "shell.execute_reply": "2021-08-07T18:37:27.517098Z",
     "shell.execute_reply.started": "2021-08-07T18:37:27.497879Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>label</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>000005.jpg</td>\n",
       "      <td>000005.jpg 012306.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>000011.jpg</td>\n",
       "      <td>000011.jpg 012317.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>000012.jpg</td>\n",
       "      <td>000012.jpg 012319.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>000015.jpg</td>\n",
       "      <td>000015.jpg 000418.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>000017.jpg</td>\n",
       "      <td>000017.jpg 012331.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4815</th>\n",
       "      <td>016148.jpg</td>\n",
       "      <td>002127.jpg 016148.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4816</th>\n",
       "      <td>016154.jpg</td>\n",
       "      <td>002131.jpg 016154.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4817</th>\n",
       "      <td>016168.jpg</td>\n",
       "      <td>002137.jpg 016168.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4818</th>\n",
       "      <td>016171.jpg</td>\n",
       "      <td>016171.jpg 014843.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4819</th>\n",
       "      <td>016172.jpg</td>\n",
       "      <td>002141.jpg 016172.jpg</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4820 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            name                  label\n",
       "0     000005.jpg  000005.jpg 012306.jpg\n",
       "1     000011.jpg  000011.jpg 012317.jpg\n",
       "2     000012.jpg  000012.jpg 012319.jpg\n",
       "3     000015.jpg  000015.jpg 000418.jpg\n",
       "4     000017.jpg  000017.jpg 012331.jpg\n",
       "...          ...                    ...\n",
       "4815  016148.jpg  002127.jpg 016148.jpg\n",
       "4816  016154.jpg  002131.jpg 016154.jpg\n",
       "4817  016168.jpg  002137.jpg 016168.jpg\n",
       "4818  016171.jpg  016171.jpg 014843.jpg\n",
       "4819  016172.jpg  002141.jpg 016172.jpg\n",
       "\n",
       "[4820 rows x 2 columns]"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_submit = pd.DataFrame(test_submit, columns=['name', 'label'])\n",
    "test_submit['label'] = test_submit['label'].apply(lambda x: ' '.join(x))\n",
    "test_submit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T18:37:27.519258Z",
     "iopub.status.busy": "2021-08-07T18:37:27.518848Z",
     "iopub.status.idle": "2021-08-07T18:37:27.744171Z",
     "shell.execute_reply": "2021-08-07T18:37:27.743231Z",
     "shell.execute_reply.started": "2021-08-07T18:37:27.519232Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "test_submit.to_csv('submit.csv',index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 319,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T16:34:21.889313Z",
     "iopub.status.busy": "2021-08-07T16:34:21.888736Z",
     "iopub.status.idle": "2021-08-07T16:34:22.064112Z",
     "shell.execute_reply": "2021-08-07T16:34:22.063620Z",
     "shell.execute_reply.started": "2021-08-07T16:34:21.889264Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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MPHiHCJ7aKb53/hbfeOk2EzVPbZqYuhUeqQJpoREqML+6xK989Yv85lc+w/GVFqNRzW6/xJFS1QYlAkmikdKjgiAIiZWwOTJc7znKRqDrCZ+87zCPnFvEaRg4hQiSTAqmbQgEJAGB9wEXJCLtoAgEa2maChECUsS0ckwtvzvr6heRRr8dM7cPG2b89f4fa8ZfM/56q3i3+OtjKXV/3/AT0sLwU1JDAWG/cjpNDQsQIaYa92//eDzmD//wD3n6qadoGoOzDgEUeU6wBuE9h1ZXefjsWc4cO87htUN02m10mhB8oHKO8UiT+gRHhrcCgiRIjXUW6wyJAhkCKgeEx692sUFze2whePKsoGkM3jnSRBN8oGkaEq1pFS2qpqYqS0KwCOsIWiGV4vbVC3x9Z5P5pSOsHL8PsiUmwyGNHTEpR/Sqko4bc+ZIi2bYwxjPuBrQ64/IWjmLrTatoiLPcpIkwzYZSaJBQulTnr1e8fXzu/RDBzeZkOmErLOEbi1w+MQJBqMJUiQ88eRn+eqvf56VtqSpDKaJrqrWWIosI8sSpADpQeKROPJM8/Cjp2gubDMZlJy+52G+8vhhlJRc23EY4zixlFPIGG0Fsa8KAakE0ifUXsfKeQbWQrAWKQQKi6KJ6+NO29Z9D4/pGkC8IaqNmDaPHqybn1hqB/hYP3N3GR/raznjrxl/8dHhr3d98/OxJos3gUDgADmdtSIlOAHCxx268gEVAlZ6AjLWXUXAC3AefvCDH/Gdb38XKRXOVjFtqwPO1Sx22jx06jQPn7uXw6trdLpddJKQ5RkigHeW0FiUUkit0aQ4JQje471DWkUaNMYYjNQEYehIhRCKuhH0yh3GCExlwHtUoinLMVmqI9k4j5IKIzUySanKkkQIhNAE75EiUE/6bE6GDHrbqGIR7wPBOaRUjHvbrK22CLVkUpa0ixSsY2N9i2W/TCfPCTKNzY4ugHcE57Ay5bUBfO+mZxQKTFPRylrk7S5e5jir2Lx9i7IpSfMVXr+xzbeeuUKmEz5zbplCeRItyFLNcieh0JHYpY8RUwgSaaAIgfuOtGkfa3Fquc3uuOJHz2+QduZ56OQSUkgIbnpfBcGBFB4fwCBRRPKeWIELBVniQIITAWdqdPCEUBPw0dwMhxCK/SaBfVFsOFg/0xDtDh3GwShDEaJoNcRXEsLHn/iYlLXuFmb89ZOY8deMvz4q/HXXHJ7vdsr3rfzeBz2lvI8gAiKEaSpSxPEr3qO8x9sKmaVYofCI6Bsx3UnHFKxib3eX3/sXv8dgMKRqapwIBOFRzrOad/jMQw9z3+kzLM8t0ul00EmKVJKptIBgDDiDEhCkRGoNWuHxOGPwQuD9NHaTAi8EiRDkPrBQ5MznCePKYNDT9erwISCEjOllBKNJhZaCIs0I1lE3DUrF4YJhWpc3pqKqKpKsjw0KqQoW146wtLyMlBWj4ZjBYMjpE+fIEvBNzaGVZebn2mRpRp4m09dzeCUZ2oRv/eAlbuwmmKDIii5JltJYj9IB6/YYj8dkeZe07bl99TL/7Ssvc+7ehznb/TQP3XOYdqdF8IFMTx9aqQhTLxIZHHNacGJBslS0mdSOv/jhq3zrey9Ae5GvfOVJAoHaOVpKIITFe6hsYDjxTKzn/KsX+dH3v82la7c4ee+j/M5v/xbHV9skMmBcwPictg4oofEu3qcgwAUBwk0/ckJcF6hpRG2m0ZQC1AFxMPUeCUjw0d+Eg/Q0vJky4+PyIT/jr7ePGX/N+OujxF8ztdd7hP10X0wFA0Egga0b19m6coVyb5PW4hL3PvlLuLyLDBJBwEmPFIrRcMzTT/2Ay5evUNUVUqu428ZxdnWNzz78EKdOnODQ6iHyrEWWJnGn7T3BNZFAmooEG+vMIko+IwEIhFI47cF6tNYwNQWTSoEQzLUCq50O66NtDIY0y3HeoVVCCBJbVRxbXSAXjs1hhbWBRGmMtBhjgKiokFJG/w3rkK5G64K0yGl15lgoNIt+l97uLUxlOXzkCCKU1OOYAhYCnLX4ROOCA+HwquDpl2/yyuVb+GyJdOEES4ePMxnuUO5t490YIQ3tdhdlwQw3uHrpWZJ8kV6aMJc9wVI3R2oBSLSI1C3wMfrw4AKYAFXjOH9hnT/7+lM8/ewL6GKe0/fPs7PTZ3s+RQbN+s09Xn7xBV65cIlazJEtHqW7coSv/8nXee37/5ogJf1S8MSnPsVa9whaGaraYAJ05nOKNEHKjEZIeqVja30LzJi1pTZZJpAhIEOMrLwQ+/ZoUzrwIBxBBIJQCL+vyvAHJYtZ3meGt4MZf83466PGX7PNz3sEAfj9ZJ8EHTzrF85z+dkfsVykJP1trl88Tz0e89hv/HWcyhEh4KxlXNa88uLL/Bf/r/+C4XCADx6tFGnwnFhe5JP33sOJQyvMzbXRicaHgDUNwVpCcMjg8KbGNzW2qRHeRPOq4OOsl+liDLF8TkCglY4nLaOcsJ17llptWnKXoQhYZ+PcHSmxARpjaGvF4sI80ktuDMcEqUhDekAeSZLgvSeEgNIKFxzeGay1lFXDQi4IpmKv10MIuHjlGitLBU0I1OMxVVMxl2ekqYLGI5Rke1Lx9EuXMSpDJxlrp85x5NQ5nn/qz7HNODqrJjnBCpA1GzeuYOoRbe05c0hy7swRtPSR0IWctvjF7GrwnsZLBkZw6do2f/rn3+Op7/2IzRs30DqldazDwnybxeVVXr+1x3//336NS889z8bNi1hbk3bWaK8e5+ipM4z3tllYXGFnb4fXXn2VHzz1fZbyz7DS0Tjv8AJq2SVJM0KecqtWfPOHN/jzP/h9tq++zLnTR/m1X/08Tz7xCPMdjcfi0UhAhFint4BDsd0fYa1gdWGOXBlksISfiKxmmOGtYcZfM/76qPHXXS97vVsj698vt9S7daxY4ZQgBcLVbF26wPVnn6ZVDrC1J5GBTuq49Mz3WD1zmsMPPE4IgvFgyOvXrvOP//E/YjTsU1YTEB5XO452Ozx66gRrS/O02wVZluBthQiG2hiCN8jpssEbcBYZDAgfpwGHgBfRd0IIQElAgYyd+84LFBKdKNJM0ylSOlnKqHHUvkYEiXcOicAIqBvL6sJ8HA5IYLMyWB8O1BN1XaO1RmuNtQ6pNIJYsx8OhmR+AvUWpXV4Ifj+sy9y+NAC7SSmoNu5JMy1cQEynUKS88rNXTYHE7xeQHcWePzzX2Rnd0BTVwRrkEmCkBIfDOPxHtVkCxkCi23Jf/YP/ybdIkFF8Ws09yKqHAalZ3ds2Rk3PH/xBt/9zo+4+uLL7N28AK7C6AK7rnn15RZJK2fn9m2+941v0exdpynXwUwo+zfZW3+J2xcydNpCpm2OHD3C0soal1+7yDMLKZ948CytVkaW5XgLlTdMLLy+ZXj2uVd55YUXcYN1dm6v8+PnXuLRR+/n7/yt3+Dxx+4ny2WspAvJuIGNQc1Ll2/zwsuX6G3v8Wtf/DRffvIsmXLTWnlMH+/HWW/2rL7d5/jDghl/vb1jzfhrxl8fNf6aZX7eI8Rn1aO9Z+vKa1z6wXfJqxHKltR1SWUa6mpCETzP/tkf8VtHTuBaczSN5Y//+N9w6fJrWG9RicQ1hm6Scu+xo6zNt2nlKd57zHBMkAKkiNGQiM2GIXiCt5FI4gAZpAjTOTVT+W+INXIpQYVA4x3SxSZFIQU602RFSjvP8JM+QWqyNGFc1/i6oUkVN/sjlrstilSyWKQMjMNoTQjhwD8DYgSFCJT1hDxtkSUasozKGrZ6I7rdLnlesH77OqNmm7lWm0wL2pnA20B3YujkGT7vcv76BoYUrTKyvENZTdjeuo2wDuHBC0njA+2WYntzB0JsDvwHf/9vcd89Z3AuMqeTil4ZmFjB7e0Br1y5TtaZx8sWP768x8TlDEdjvKlwdoitxpRVBXjuOXeOSX+HZnibanID54Z4VxNqQGiE67I0t8AvffGX+OwnH+HokaPMLy3RKRIW5guKTJPqBCUVQQq2+vDMj5/hlR9+EzveRgSLEDm1ETzz4lUuXPlnPPHE4/zar32Ro8eO0p+M2B1VyHyebPUeHv7sSfo7PV59/SKPP3yC1a5EBEWQ+4nj/abCWSZohl8MM/6a8ddHjb/u+uZnRqgw1fzFZq7gp8whUMKzd+N1Ln7/2yTlgGBLalMxHo7o7/RIUkgTRbW3wTP/7k8498Vf5zvff4pv/sU3Mcag05RyXCJcw9rSIgtFipYB21Q0I4FOG6QSGOkRApRUsfYd3RqmMsT9mut+8T7W7gPRZIw7jMy10vhgo7uqjHVkLUB4j9IS7z1JovGNwwfJ1mjCzmTCcirppIpuopkYh5TRKyKEgJSRSELwiGBp6jEqGZMXS7Tmu/R3EkZ7fe65ZwWDxhuY9EtaiaRuSZrKMZ+nLM5lVMOazd4ITwrO00xGvPCD71GWFRoIMsELRZK0kFIBCUVrgYcfOsNf+5u/gwuCce0JUtGvLZdu9bi5O+bKzW2SLOFz55bY2qhw4wnXL7/KaLSFDIamGROahhAGDFzFpWe/i3UV0u1QTXYIwaF0gkzazC0f4b6HP8Xf/wf/gC9/4TEWCw1I0BrrQcoQr2mIad/dieOlK1s888xr9DY20FKTzq2hdELQBXPLhyi6c5y/bbjyL77L2Xvv4Z4Hz7G8eojuXIv5NCdJFPrcEYan5vAEgtDTmsCbaErvXLUf0WzPW8GMv2DGXzP++jjw18c+83PXHW6nLyeDhCDxIjqKSgSj2zd55VtfJ20GKDvBm4a6qqiNoVdPmCcD4UkTuPHiD7jZn/An3/whw94eIWjGZUmwjoVEc2yhTVsBjcGKIcbW1DaFRKGkIFEqPjBJGkkixI57LQLI6Fvhg4hpRx8OLN3jV4yuvAeQMfJyoBGkCtJEovMMYwMiWJJUQXA0PtAvDUtZmzRxLBYpw2qCFQ6pFaa2hCjcQEmFEileCEw9ZM71ObR0iEQ+wMWXf8RTP/oR3nvmF5d55LFHkaZi9/plmqahtp7GQyMEZWXwQRJCRTXcoLk0Jknb+GAQicJbw9Ejp7hx7VUIhlb3MH/nP/zf0sic7UFJ4wVGaHaGjhdfu4HxKdXE0M4LhsOaZ599jlee/QHD9auEuk813sbWA6w1BARVr88L317HmAZrhuisTTsrSNIOtA9z5sFP8vf//b/Ll598kJW5gLeeiZGs7024ud1nvtsi1RonUoZjy+s3d3nhldfY291kYeUoSXaG7uIKjfUEnbK0tkar2ybLE86dPMapE4fRwiFpUPWEPJMsFgXzuSTkq4R6iAgWhD0Qmb4ZZhufDydm/DXjrxl/vb11f9d6fu727/y833u3Xu/n1RB/0df27BegI4IXaBkwwx7P/vnXycZDUumo6xofPGVd44FJYyjyDK2i06avPT/45re4dPEqZV0iRYqzFhUCC60W7Szaj1traSRoKaKxlUwAhQIcoIKdvjcHweGnNVMvp5GdD/j9J3raSx9n3kxr3YHpzwBKkhUFOpkwaiwhSIQUNNaSqoQk0yB1VF6YBkVgtdtGjEucq3CNI3gDQSKFRic5FodzDXt7N1nYW+bBhz7F9atXsE2Dr4ZU5Zgrly9jyzG58LQTxaQ2iCApg8BYIHiwDVmrYFz2EM5Nyc8gdU6722V3dx1hhnz+K3+XJl/g5eu7zCXxXCfGMag9zhukFOBrxuMRTz39HD98+mmGO+tQDygH27iqT/BNdJQFPCkhKE7f/2kGwz3ceEKWZASZcPjEKf6jf/A/47OffoBOLjAuMLYJ17bHXLyxSV60WExamCC5vj3hxvouG9tDNnYnrB27h/zMfYg0RacJ7Tyh00r45GP3sdDNCK7h2HKbbqppp5JMRz8Oi8DjUSGQthOMSPHWTtfkmxPHxwkz/vr5rz3jrxl/fVz462Of+flpvNO0t0DETnsRPQmElIi65qXvfJPQ20IJgxUG6w1OSsZ1gw9wa3MP6wKrco683eXy+h7XNrcZNxOkUkwmJQLIpGCp00Gzn+CND//BoL5oyYlUCqmiVJCpGZmMueGYxfY+enUIonQTjxRyOj05EmmiNMF5CALnAzYASk3dFqL1uxAS8BjnwAaqxhzU4Vt5ijISYy3GWZq6iQoJb0HoKHetDc4ZApZBf4fRcMLKygmoS2ww5Erix0PwMGpqRDtOQfZMs6BCIIwFDXnRYlxuIcjjzZCBY6fPYmxNcBUnTx3nE5/7HOev3+blS1c5e3iNdivDBRjVNY0LtOcW6bSjW+z6+hblaEg12KLcvYEtdwmunB5YQpJz9NwjHD/3afApvZefjxdZFbQWVvjKb/42Dz12Pz5YKiuwRnNzb8L60KLbCxTtgv7I0R9NeOn1W9ze3KXXGxKk4NiZswglGI6GFKngyU88wOlDLY4t5bSUp6U76BSk9yTCE7zHoWi8oHFxHg9BkWYJlY/3CMT08+Gv/pCcZYI+nJjx14y/Zvz1IW94fscP8V2I8N7WB0AAEQKIQBAO4T2Xfvwse5deZV45BAZjK2zwGAejsqapLRvDEpsUOG3pbW/yzNWb7NaW2hiUVKRJgqlKWkVCJ0tRU4MxgkIg0VqTFQV5lpMmmlSraXOgQxJr6EKoWEsXUR/gfJgSACAUQoKSDiEhTB05sX4ahXiEkLHZjygf1VoRCAghsMaAUOzs7eJWOhRZwqiMU5fbqaY0CQMtqSsD1pGkHu8MwQWYLu6qHOHMhJWVNXZvX0EDGQ7Z1DQexpOSUW1JVhdopQotQDEdtOeixX3MeDus8RgCK2uHuXLxNRIZ+OxXfp2x9ezt7nDj9etcvXiFMyePolPNqJzghWTtcEO3O49oorFENRpQDbeoJzsIV+K9iTOCsnlOPfpFHvjcrzMsNesXX0M6aJxhcfU4jUhZPnSE3VHNdjOhlWaMKk/lBSpNaSUwGk0oJ5Zrt3dZ39rj1tUbBGD16GGcsFTDMZ0i4dGHznL62DyHupJce1Il4v10sR+jCRIX1FSZEvAifng4IRAhJc07eFvirAXhf65J6qzn5e5gxl8z/prx1/vPXz/vGbhrm593wwX1nRLA+0JAEPsFCSgcNy+8wuvP/4Cu9CgsPhiCsyipqRpPWRrWN7f50m/8Fk8/9wK76z22y4r1YYlAo4JCK02wBpSg0Ppg8cSeRDF1IM0pioJWUZAmKYmWqODwtok10+AP3pMgIMV+ijuetSBGWYGABnyQ+OCRMqAkKCniELvgwXuEiD4apqkJwRGCx9qAEwGlJHkmQSh8cLja01aSllZMaLDOYaxFSRENyYLCec9oOKDX22DSaEKSU/lAFkALj/We2ltqE7i5N6bTOUKmE/Lc06vGBBxJkiBlimniEMMsn+fq5de4ff1VOt0WJ+99mN3+gOVOSn5shes313n1wquMxhPGZUXe6nBqZLj/gfsxxtNMxtSTPs5MUMLQuBoXAmnaprVwmEef/FVk9yi3Nq+Dd+AdKslYX98k7ywhhGK7X1GXhlaWMGlqtJbIpgGlqBrP+UtXuXxtgxAUtrJ057oM+j2OHF7k3mOnObwyx5GVNqstRS48TeMYmIANEoJB6wSkoCprpPe0s4Q8VwgfKI0jEdDOUxIpkKLB2powLSXcrefko4AZf01/B2b8NeOvjwV/fWAzPx9o7G8mf3KyX5zfRiBogXRw+8JFLn3/e3RDg1QW6w3W1iAESZqhCFy5vYHQCdcuX+GLX/4V/unv/k+MrUVKifABDzRVhbOePElo5ympUjENrOLDl+c5RbtNUbTJi5wkiYtFeIsn4B0E7w5SxrGBTKJUrJtPT3zqCipQSiJkTEMnXuK9Ig8JWWNQItbmRQhY22Bdg5QCKQPOO9IkI88SEuWphSVJBUokKCmprGNU1UysI3gBKCKFebyL0c7W1k2yuVMElVN7SW0dIolRQQgCIaFXB3ZczuGFBTouRfZH2GAY7m2BDwRZU9clC3PL7K5fxdV7nHnkUyRpymR3g45WnDqzxtmj8zz36g0GwwnjYY1UbayBnZ0Bvd4eO+s3yVNJowX9pgYgSTN02ibJF2jnc7z44+cpBwP6W7dJOnM8/NATXLn4GsvLq6gs5/X1LcbDiqXuAiqVLLQzpNI0VnBtfZeLl69z7OgJrrx+DZElLKwuImTDA/ccY3W+zVwuWWkpFnNiWl5oticVO6WhMhZNzfJczmKhWGxldDOJFmCns4tCgIAniASVSKQUOFdjrcV7P1XI/GzMNkYfQcz4a8ZfHxP+kvJn9wm9r5ufu02s7y1Rx7SqEAEZYkVyWsFGWMvlF17k5gvP0/JTh0oZM7BeKJTWoDQqFQitkWmKNIZnvvMdOkXBZDTCB0fTGBCaNM8Zj8c425DKPD68xIc+BIGUchrdgBJMpaHTr+lYFKkUQk6JYjpJWRKN0COBeEQISC3xQhOUIFMJaIPQliCgbjSZFigF3gbctGbtvEcqTaIDq3Ndiul5ZAKCkhjn8FLQThStRONlINEJ1vnpLn469C5YdrY2WJSLVJMK62ASLB5J4+LxEB4vFLUsqJIO7ZWCfHuH0aRm0ljyToemaqb9j4FRfxepFY988tPs7vXpFG2WCkUn8ywUKaePHWIwAUOHVtHixtXX2dq8halL7HCHSe82/d11gg8kaRulEoRMmFtc4fq169x67SVyHI3xfPGrX+WXv/QF/j//5X9FyDKubmyztb3N9sY299z7AGtH1+hNKkQp2RtNWN/Y5cixmLbWuQbvsMJy35mTtFNNngSSJGCCoWokSkrqALvjkqHXjGpYThwrLcnR+YSWBhVij4OE/c80CAGlFMYGxlYTZEKWWWQ9ihLi6WrZj65/YpXPen9+Jmb8NeOvGX99ePnrfVd7fRBe7+1AcLDk4wMpoyGXtIZXnvoeN158CVmOSIoY5WCj3DJNWiAlQUhaWcqvfekLBKUJQvDSxdcZ1oatYR/rHNZ72nkSpZuAEoFMC4J3hKBRUpJoRSpBuhqMwEuHcBonRSQS4RByPyJSBB8iy0ybAsPUMAwR/+6DwkmNVQKhoneGEhLlPakxpJmOPgwoUpXinKSsG6RQ5DqwNt+hLRXWGTIhsB4a7wjekUhJlmiqEPDeYqyNaWwRI8BESHAGWw0x1QSEpPYBZ0xMZssEgkECzge8zlAJnDp3jpdffo3jZ+7lnvvv4/bNq7z60qu4bI65wznz8wXnHvoEF6/dotfbYSeU3H9iiZX5DksL8xw+nuLTCVvXrrBz+wIiWLSCZrTFaHcdLTwyayFVilYJMm2hE81rLz9HKHexeI6cfogvfelztDKNMxVV1XDt8nVeePopJIHO3AJeS4pWQWPiB0OrVaBViguB5ZUVbt+8Ac7TbXWx1pNKjRKCqqoItScvCnYnNVIqUh/jztW5FmstTVsEkmkU74NAi0gLctorKIJHK8lOLXnh0i3uPbHEycUushlBiFOgw75BykcYHwS+mfHXjL9m/PX+89es7PU28cacEYGT0W8i8Y4Xn3qKKz/6EUXwJCruRiejEdoHkiTBocE4wKASWOm2psPiKqQSJEWGDXGOjpSSuirxXiAcFGlCrjVSCoIEJQOZ8qTSo4MlNCXOG1AKlMRJUEogpEAKhTzIcotY556S3/578UJikNTGUfmAsZaqKuNid56JDYybgHOCZDo7xwWPVoLgYurX1BXeFVG2GgKJ1iTe0RiHUmJKUAE/TVs65w4s472P0tfRuId1NS54rHU4KUjTBCkUzgqkznD7UaOSnD59ivGoQohAXhQ8/uknaC8eIWkdYmHlEMdXWswvLNHZ3GGrMWzubpOEitVPPEJ7aZmjiWBUXuO1rds0/R1UqKlMTVP30RKUSlBpG61ztEpI5w5RlZZq5yZSBEzS5uSJk/jG82++/qeMh0P6u3vsbmxgJyVFZ47NW7dBaY4dP8F4PKE/HCFQKKVYXlyi7A1oJhWHVw/RGE9/XJGlkkNzOXN5SrtQ2BCXzly7C8OKouVZ7mRoGcsCYXovfSBGTwKkkAeOuYmEbjdj2AReuLLF0sIZ5pIAzQSB268ezPAxwIy/Zvz1ceevj9zmJ4TwrkdPYb/JLkSxphcgcfTXb/HS09+jjcFYS6fTwhmD9gItFAGFDRLnLMIbcgEOD0LiqppgLZub21gvsCaqFKy1OC9IRaBINFkiUQoSJSnyjKKVo5J99YMBY8BJRDJNE/vYUBjUGxLQEBx+Oq/Gh4BH4EKUGA5ry+6kZtQ4JnXNaFxSNdHkKyDZHhsmBipX45zHCx8b/6RCSQ/46UK2EKI5Wqypx3tijMHYqWsnHBDGwbTkEPCuIc8Vpg6RRNEoXWBNjVACneQENI1xZEsd8qLg4Yfv5/nzl3n6e9/ikUce5tDKKofPPMDR0+dY6wi2bl2hrmvK0ZBxb5fi1BpzK0cZlRlmOKZpJrQ7CVSaejQk2DHS1wihQCQonZLmXXxQnL7nQW7duI4SEpKUtVP3U5YN//U/+q/ZuHUdN9om2AZT9snSNt61yFRCO28xGo0YDIfs7u1x+NARTp44SVPXNE3JI488RGUtr12/xdLSPDvDCfk9R1iaayGIapHaOiajISJ4FlsJbQUqOHAGExRWKkJgOj1ZHBCCFAJJYCmFLzxykqvru3gPSZbhXENwYSo9/knMen7eW8z4a8ZfM/66e/z18/Ch2/x88Mg42qYra3j+e9+CeoiT0M5zgrMwbdxCaRoPtjE0ZYm3FYNg0SrarA8njsm4YjAaU05KpFRYZ6mdJRBIpaTIMlItKfKUuW6XVruFTKK3hfEe7x0J0wfdC3SqUDJ6XfgQEAcE4g+G9TXOUVtP7aBf1tzuDbm53WdkApV1VMbhUCjhSZVmZ1RTeTAuvoZUAgJIJVFa052fWpJP/TViLd5P08/TyMkHVCIPmh2NMdH+XmukDHhb02m1aMqM0llUkhNEdHRVMkEIjfMwKiusn8OFgM4zTt1zluefO89ffO1rHD58hL998jQLhSMVgb3dXfZ6PW5fu4Ssenz+s/8LrOowHJfcvHqdS+dfRoUGFxpMMCDjHCHvPbg4KDHLC2qvqSZDxqMeXuecOHsfc8tHefWVl8gST9PbQNkBLjQ4HOgUKQVbW1uQ5ywfWmN1bYWslXFoZQ1cVM+cPH2a2+ublMbTnluiDiVKBFYXxyzNJZAKrHXUtWVS1nSKlFwFUukR3hCkYOQ0vbEjTRQaQRI87Sz6pQQADxmWw21FcniRLHi0ECid0AQHwc96fN5lzPhrxl8z/vpg8Nf7InV/pxOO3+z77z1p7xcYAxrB5pUr3LzwCi3pmCs6FFlGsAalE7yMg+d8bXG1IwDWeibjEWVZMp5M2KsCl3eGDOqYLtVSkxQt0jyjriekAjKlyLOUotNBF22qAOOqQQpIpUB7S0qss2dKkgsR04F4hDDTB0/iQ4xYnHfU1jEoa3qloVcaNvsTNvtDhmVDYy1SaRCKVAmsUFTGkRYF0lr81CLdWYtxDoFnNKmoZYoS0xps8NOBhLFpMUZIYSrrjJGSc+6N+r2U+KbBBoUSKqZp0xzvPUrK6NbqonLCe8iKNkEluCDZ6PU5evIM9d5tdjauc/PySxw/dpihMfQGQ0aDPXrrN/jP/3f/CcdPnOKp87e5dXOD3sY6oRqyfesqpu5DcLGGLMRBI+Nk1KPVXaK7uMrG5m2CCDzw6CP83b//9/jn/+KPCFIwKSfUTYUOTZzc3J2jtXSIpLVAWrQQUrF66BBZK2dxeZlMa0a7Pa6+dpnLl6/SNIal1cOYicEh0FpwXpe0OMyplQ6VsVRVQApBJ5N0Cw3BYVxg4hMubJfc3tjmvjNHGA5GHJ1rU6QKhY/E4OVUwhxYbEXy0cLgtUbaKNf9qE91/1mY8deMv2b89fHirw9d5udOvH8EPW0UnGoOXFXy3He/SxoMRZrE+q8UyCJDeI9wAYyFxiC8x9YNTVWjdUqrnVAa2O73uTWeUEtBUBJCwFlHYy2ZSikEtPM2adaiCYrRYEzVNJjgp94VjgxPJ5GszHdYTGIdO4SEMPU0ldIipcIHBSFgnKWylkltGExK9vpjxsMxKZ5D8wVZoui0coosxwvN7Z0xg609lIyEoaIIEQc4FzA49gZDbGsxmlF5gXf2jfsUPFJKnGsOUsUQPwz2icRai0TQ+IbgA0popFB4XJQ1CglCYpuGLFumMzePcxWDiWFcwdHlef7z//TvsdCSbOzVXLh4kYlT3NrY4vKrr9DJFI889ji9seHW5h7Xb16jrPvYZog142isFi8WVupoxhU8+Ibe7iatlRNYoTl+7mE+/8tf5MEHT/HpX3qSYmGN9SsXKcsRrpJIEhZWTnPs3EPkCwvorCDNW+gkw3mB9vDyCy/x0o+eox6PmQwG0btktEeSF6BjeeBivcacqEj9YbIix4WEbt5iPknJZCwpDEzgem/MU69tcWRlnnFlGdaeNE8RIUZWB+aoCBSxfp6KuDLiAMWGgDlohP3gZSg+epjx14y/Zvz1/vHXh3rz835hKrDECYGWnpeffYq9GxdZ6RQkicIYg1ASoTQIicAinCOVASUDVnjQoKREJgUhbdH0G+ogsdYghcCGOESP4Jhvd0hMg0ozRk4y2O7RH02oLNggCM4ghadIJN1EMTYe20mw1tD1GamaGnxJTZAatAehcSFgjKUux/iyJA2WlXZKutwl0ZpMS1p5TpoWNCLj+nafUV1iVYpA40K0tg8ElFDgBc6DShK8raIJGYIYqsXIyHmBkOonIialFGKaUlYqemdYX+F8Q5IU0dhcpYiQErRESoWzJVJ60AnGB2okWbvD4mKHpcUOn3zoHiaN4Pkf/3f84JmLbG6ts7dxhcOr8/RGE/aMY2dnj2o8Ym9jA+EdeZrhjIkEpRQCF1PgHqQz+LrHsHebleMPsbp2jNNnT+CThPsefoSdoSdNMlrtFk05Yn5xhbUjp2nNL9GfTOgPhiRlzWhlFZ23uHbpOs9++9vs3bxMK4uGbHjBeHQbJ3xU1DjLYH2NI/MFC92M46eOk6ZJFLsIh3WWstZc3XF898UrbPWHrB05zCtXN/jUvYfJErDBIwIxepKa4EFLhxJRIurElMCVxtSQaAH4g5U+w0cPM/6a8deMv97i5mdf1veL/uxbxd2QgL6b53cnghckUtC7fYMXvvctWipKOY2xpGmOkoJgXdx5Exu46maCaRqUCOgiJU80NiRUw1H0gfAeSbx5Uim8iP9WAZTSVF4w3OkxqWrK2uB8rE0rGUhTjRGKsTVsB0vSpPi5HB8c7USRJRonA0pBmiQIrVDeowQkBDpZSpHmeBEHAzpnI8dYh8MwsY7+cIglUFUV0hMffkDpWPdXIZAmCVIprJvGlmK6ZQ8OiAQRpvV9MV24zrmp7XyED9G6I00KQrJIyBdZPXKSYW+AwNGUI4KvaCYjNKCynOV0DnTOiWMrtPKCEDxFovnrv/UrfP3r32K0t0eaFGxu9/j//f6/4sS5RxlsbzHpD2lKQ2UCLilod1tUkz1MOcJaS5bnuKDwSEIwTPpbLD5csLu3ybiq+e7TLzMuJRtXX+PW1auM9rYpihbtjmN78zZ2c4O6saRFm7GT7D3zAitrh+mv36LaXYfJOnVVg8pQqiDVyZRUFSIIEiXY2dnl4qWUo6fPcfvmJu1M077nKGUp+cY3n+HV62N2x5ZuN+Xb332Wh+89RitNKMsKKz2dTCOVQEzTxtPpSFN/lJgFyLTCaR2HKapp4+1HbPMz4683MOOvGX993PnrY5P5uZtp/KjEE/hqwg+//qf4YY/WQgulJIlKEEqi9dRZ0kUFgQ8OrQQilZjGYV3DuG6oXUKvLNkbDqmNwbiA1jH13DQ1zjuUlHjr6Y3H1KZCC8FcntDSikyL6IUgBM55cA6sYTAySFxUCbZSPFG2WSQpSZKj0xSBxDeGTp6jtadsLGVVUxsHSGxomJQG6wfs1jCparxz4GLNP/qLSbTSKK1wdcPyXBctJXFYseeN4MnjvSAEf/BVFK2DZkHn3EH05JwnUQorc+aPPcSpT3yBE/ecY9jbpR73eeWZp+ltXKPIOyy026hEkRQdlhe73HvqCIlWKKXBex657zT/m//Vf8B/+f/+bzBNQm0Mf/xv/5hzD97g2MkHyKSjnUuyfImsc4rgDHu3LuMbQ+mGiMZTtBexSlNXI+rxAO1LHnzwEfb6I/7gX34NVxn2tq6QBqI/Rdlw47VdhEoIKIROWFg5RMjn8R5e37iOn+zihtdpRjcRwpG0l6MctdUhy9u0u0s4a1BpSn844WSxwM31Id/5/o/56q9+kV4V+PFLl/nXf/pd8mwRZzxl4rlUjnjo9N/jxvaQlW7KfOopEFROYIwhz9LYDDk1BHPegZBoEfMBcYPAz52fM8N7jxl/zfhrxl93l78+1Juf97ov4aD2K0BKwevnX2bz8kU6qSTNYnObQEbHSyniwDo8zlmcMxgbZ5MIKVBZgvHQG1pevnWD7X4PoTTeNHhjqKsK5yydIgMf/VeDt3QyxWKRcniuw2KRkaqohCgbR2kcxli8VYTgMS4wLhu0CMh9CW30lUcqjZQGqUR88BvLpKoZT2rGtWMwKqM9fJ4QlKRfB2oXMI1Dq4ykJfECqrLGWYtMJN12wdJch0R7jNZ4a3DB4YLH+Tg7x/vYFJhlWZSq+riIrbUH0ZPSU4v6bIETjzzB6cee4OTJwyg3YWN9g/FkRGdhnsW5DJ1mLLY18/MFSs9zZGUOSVz8PgSkDPztv/HrXLj4Gr//r/4UJRRBOK5cushkbPj0E5/g0d/4HNfXb3Nrb8LuoME3DtcIGtNQ9ddRQGtuCS0yrHF0c80nHnqAP/qjf40fbLN+9TLe9tHtRRACEwLGOpwPUQYcoB5sQN5CK4FvRox2blGNdqKlSdYl7awwf/g0C0uHqWvHwtIqg94eeSfn6ImTrBw7yfWtHiGdY6vnuXHzEj96+kcMNzcZ1Ffx9YimnlAsrnLxlQs4f5pPPXKK+ZbEBseoCUwqw2qSknuPlXG6tZj6obSzWO5QiYhRLWK2AXqXMeOvGX/N+Ov94693tPl5N4YB3o3Xv1u//2avtz9PxE+GvPzD75MLS6edoRONFBItFVIEvLN4Y3GNoWkqqrKiaSY0TUWSZ8wvLJNmOTs717myswdpBrWN6eIpWSgp0Cp2sacCWlqw0klZ7eastjWdVEyln5JMKRLtGXofU6AImiAojUNXASUVRStFpy1AxNSkj2lt5z2VMZTGsTexbPdGoFNUljCyjvGkZlAZxrVBSIkxDUIm+BBQU3Mv711URXiDIhKSlZ6mMdTWYX3AOEcgShO1TqjrJspNp82C+9cXAUJLss4ci2uHWVtd5MRyjraOQsyjH3+I3RNHcWaMzDKKQjLf0jFixSL2k6NSEYIgVY7/w//6P6Icjfnmt75Ff1QicEzGA370/e9y/8k1zh5aYKFbsD0OvFiOGY+GNHUPX/aoRkNM09Dpdmm3C778pS/wb37/D3juh9+iUAJlR5STEVlaILzBWRMn/gTwPpYDmnEgiICxFSIYEhlT7CpfpLN8nO6h06wcP4sIikm5HRs304wTZ+7h+NmzhCyhdI7BqOGpp56nv3GTvRuXqbZu4ettgh3igiNNA88+/RS3dwYsz7c53prHCUW/hEkT6FqLCgavFaXxZBKQGuc9Wutp++f+s/PRKnv9NGb8NeOvGX99tPnrPZnq/nGAn15gvOPC8z9isrPOcien3coQSqOlRoUYDbjGYE2DMwbvHSqVdFpz5PkaxlomjWWvv8fN9R1Gpccrj/MBIQWJivJSW5cxjUqcNVPISCDZ1Jui8YEQJE1jqb2kX1l6E0NVO6x3KBloEoWzCUkiyDrLdOdXMZM+9XiEaWqcbfDOoXRG3i5wox7kMUXdVBOSVpvrW3tUjaMJAalSCDGqEHrqw2FD9LnINIWOZmFhGjEZH2icw/jApG4w3hOkinN/ILrGTglECDH9e4JpLKm3nDq8yKPHF1nrBLzRtCnoysPcaucMxn20bEjyBJ3mOAJhOnsoVoU9iCitXFzs8H//v/6fePXVv8Z//8//B7739HNYX+NM4M/+5E/5h//x30Mrjwg1J48uMB7uUQ06lKqNzBJ88AwGfT738MOcOn2My5fOMxnsMXJjfBDMz69Q12NEqLHGHESEIXj8fqrcW0RQZEWOlApVLJB1j9NeOkZr8Qgi65AKQafdJvjA3NI8p8+dJe/O40WcZISz9Ha32L15mWr3Bq7awZsB+DGCQD3a5faVi3hV0B88Tt3MkUjFeq/Ci0B3VKMKyd7YsTNxLBQJ1tSsFZ75LMFZF2vpH/GNz8cRM/6a8dfHjb9+XgDxgd783LlrezdTxD+9N9xXCwaxL66Lf8advaO/vcVLT3+fxVzTLRRKJyB1lBk6R/CWYKMsNEkVRZojkwSkwFqLRRKMY9AbU04MwiuMs9MDx0F7pmkwdUOrKPB4VOziwlrPaNIwnjRIKWl32giZ0VleRYuU4Y1bTOotRpM+ifC4VKOQHMnn6cyvEVSGDANCYzFVjXUWbz1apeQqZVLV7PX7kCXcc/ZeFg4d5ubX/wIpLNoHvH/D8VSn6bQPUOC9IVUJaSKi02aA6MkpsC6mnCe1nfo/JDjvCN4fyEXvvNfOO6SC+Zbk0/cd4txahnYlVmoKMtpa4l2NsxNwliRtUTlJkBKhU/K8mN6xqaRXxDR6lgkee+ReHvl//N+4en2DW5s7DKqGP/yDf8WPX/gxv/S5z9BqGZRKqEZj5rTkhvI0psFUY0y5x5e+9CW8tHz2l57geeXY628RZIEKGjO5gXGT6DobfEz3h2jaHkIc0qh0C6naBKlJW0uookNIc9pLq6i8Q6okS2saISXnHryPzvw847JmXDb0d3soV1P316n7N3HlJq7pE3yNt5ZEK4It0W7CXKHpLswz9oqNzQE/fm2bUyeOMGwJvNI8d2WLvpHM55rb16/x5cdO0zmUgRCxkTOEg4bOGd4eZvw1468Zf73P/DXL/Pw83ElK8UIFEa3fvXTgLToogohNcCJ4nvr+U4wqz9xcDklUMogQcLbCB0sIDi0FKs/xSQCtEV5TNzV1XVIOSoajmrL2jCpLkiY0TYO17o7TknipcVP9hCNgkAwqw3BSstCdo0hy1nsVt/c2mbhb2CCwpiHVAmMFaI0LglarzYkTJ8iyFFvX4GKalwDO+jj4z9T4puLcmeMsry6xtdejHgwps4wjy4tcuXaT4AJSZ9GePQS8icoHgI7WHF9cQKl4rhKFQCB9QIRA46BvHI0L5LjoPjqNlvaHFlprAZAKUIrFbsG5Q21a2iKkJA01iZSkIjDotri1O8K7hjTLqaqavEjQ0qOVByEIJIip+ZiaylMREqHg9JmjnDpzFB8CX/nco+zubBNCYDKZcO8Zxd/66ucpK8P5CxfRSU6eCpw19CvJa5duszTX5ujRI3QXFxhOAhs3b+FCA94Q59Lsk2J0EvEIsmQOkjlE2iLPWqTtJfL5ZZaPH6OzOI/1CVpqnAsIb0m05Nb6Jrv9EcF5xrtbbF+7QLl5C8YDaCZ4PyB4Q0Di0SihUDola7VQqebCzR7PPfMS56/c5lOfehx3do1eb8w3n3qJvNMC7+lvbHIkT7l35TQKOb1/AcEd63GGDyhm/DXjrxl//Sz++nmKr3dtqvv7JSl9q68RQlzcEOeI7O8TgwgIr0iQCOEYGMfIFXz/O8/yj/7xn5J32nz+s49x/2LOUrNBx+wQnMFKRSITsm6BTjOMaDCmoaorxuMxo+GQalwxnDhubfXZ7vcxUw+JJEkQIna1SykPGuq0THDeU7tA1VjyLMFODP2tITf2htQ++h1kqebQ4jxf+eXP86Pvfod62GOhs8ixo0eY63ZIRcC4mhBs9E4QsSYPDoNHBUfqauYSiei2mTQNW9euIeualfk59kYTglAYaxBKYY3Fe4sAtE5YmJtHBIHwAeFjqnRa1I91Y+twHtx0GrJOsgPS0FojhDgwCcMLEpkgnEV5TwgCZEoqDUFLEqVpjKHIcoLUNL6ipVSU4qrpKGBkrL//xD2/4xshRJLPEo4ePXKwHqY/DQhOnzg0Nc2Cxkn+pz/+Hs+9eJG9jRu8cuE8IkisCdiyT3B2Om8oHsO7GEEJKZEqIWnNk3TWyIoOUqV0Vo9w6NS95PMLSJ2ivAJrsM2ELM8ZlyXD4YRqOGbU3+PqxZcYb97Aj3exkz2cGxFcjcRBUEii3DRpLdE9cozXLt/mue9+iysvv8KkHNO/doEfFi36/QE7W5vkKkMmOfl8iwtn5viVz5ykm0nUft/BR3DS6Yy/Zvw146+PD38Ffnb2epb5iS4W8W8BIExJxKOJs1F6pePVWyMuXL/Kf/NP/5Bk8TSnn3gSceYM+sQiYu88/UvfoQi7JM6QFC1UnuGFJDiFqR2T8ZjhYEg5qalKx62tPbb2RlTG0xhHkqQIEVUDxhjsdGpwVVYk7RbOOGohsA7GzuBtw+lz97EbrmPHYxIJTTlidfEYOjQsd3K87rK6OM9cp4sCsA2+HhOsiQSCI1EySlyTBKFqRsbhg0OmCh0UsijQSLwLlEpSOQtIrPW4EJsEpYz+CwGJkAm4huDj7J1991PwTBPKuACpVgeNgvtEuY8QLFqnHDl1lqALYDq0TkmEBbzE+4BWEqUVo8ZihcJ4MN4h5P6RPD8P+x8gB42gdzQuxk8RjyK+zwBIVdDttjHOsTee0FpcwZaO3t5VXNPHm0hcYt+DQuo4STmJ0RAiJ28v0p5fpjaW+eXDdBeW8UpHz5O6ZrBzG1OOWF45xO3rN9ne2GJva5NRb4tmvIMZbmLHO3gzBuGiA2oI0YdEalS+yPyh04hsnu9862k2zr9CvfU6TbnN61svg8gpijaunkR7fyWp60NMJo/z6rVNHr1njWJaLglx1czwgcaMv2b8NeOvn8lfH7aen/3d63sjBRWxThjCtMt+6h8QHEEmrA8cT790k9s7DUJl/Cf/6f8SkSgGpWNp9Sg9b/Bz9yKPGqrrT7PktwlYrK/wSJrSMB5OGA9LyknFaFRRGSi9ZFBb7LS4YMoSKWPDnHPuIIVqjDm4JtYFbJCMxmPyJD6kj91znIuXLjGZjDl1eJmVQnPpx8+QS0F7fo61pSWWFxaZ787hJn20ElS1fcOoC0GiE6wPdPKUvCUpakfZOObaBaXzZP0xxjnGkzGNMRApAzlN+UqtMEJwY3ePhWyRORmbHINwCAJ6WheXUqCiqUdUEkxJUkp5R+OgQCqJVynJwlF6oYOwipZqSAQ4JE5onHMsLcxR24a9cU2iEzLrSedbf6W51ZvhJ4hjuiwIkeiC1DGSDpbH7z/F+ZfPMxotcfq+h1m/tUtpGoZbJYkS1OWEEBxegMo6LK0dpi4r6rJGoEmzFkVrDmUt3bkFbGORmSZJEka9HmVvh6YcYcYTqsYx7u/imhLXTAjlEGWj1budfrBJJIRY6gg6Q3WXyOYW2bl1k43L56l2rmNHN5C2j1dtQt5iYe0Mrhyyt3EBKR15kXPP2bNYXbA1rDk6p5HBEd5jKfZHBTP+mvHXjL8+GPwl/1JH3Bv4QEvd35PjiClhCDdt7hIENGXtefr5V/njbz5D2lnht3/7q9x3apUsgdJ6nnplneAdiwstFuYW2WllDE1Df+8VumIXWVdT63XLYDRiPB4zmZQMy4q9kWFn1DBqLH66a7fOIP0bqWLv44Ra7x1Sggse7y14RydV5IlktHmDkCUcbafQTkgTjSzHLOY5RZbSLXJW5rocX1sh05JSQJom4PMD8vDe46yNqc4QyBNFu91lNGmoGkNbJbTabVCKqm6omh6N9fEBDwHvPGhF0Ak3dnskpuTh4yvTZy/KXSM/x0Y0qVSMEoyZZpTvkIgCQki8FyQqZ3vgeObyLmeOLXNyXpIrj3WSsRUEIVme77DZ67NTWrQWqOCx8wWISFB35Iff8noJ8RvsE2XAI4PlxEqb3/zypzCmwqdzCNVha3sdb0dMtm/HFsUQ19TCygqdhVVqswMyUHTnaM0voFttEinpdDr0RyXVcABI6t4e9XjAeLiHQBMc2GqAaarYf6BSgsoQKgdpYop+6tyKVAhdkLbaVGWP3sYFJuuv4Eab0IwICFrzR1i651NknSXWL59HtxbJijkefvRzfOLxc8wvtLCjHSaVpJvrafT50cWMv2b8NeOvjzZ/iZ+TPftAZn7ePqa1b/aXzX76641F8ZfbA+9YYkJiSTl/aZ3LV7cZGc39Dz7CYDDC1xO0DiRa4FygnSl2dgesHelwcjVlIV3jFp/AbbSZXP0OeShxtsF4S2kNo6pkXE4wHkgSKlfReI9HoIQgKHVwQncqCPx0IQoZ0CKQZQnzrQ5pcGR62tWuFUpL5lot5lotikQjlaTQkvlMY8d9jLMkCrIiI0liOUMphTWGurG46QA/FSARgvlOi7RuGNUNylvaWtFNoxS0EpL9LK8Hgg2UtsFKTy8RmCBJg0BN+xCkAO/dQUS8/772U7X773m/edAYRzANL/74x4SVe3HyETrFEoWWWGcZjGsCUCQSJSSjSYOxNXoupTYdQCLCPnmIeJZv8fMnTNeNCrFq7KclBSnhkftPc/TQEf6r/+/vsr3Z456zJ9m5dYnGGnyIPipSSLK8TRApUuekWSBrtekuLscIR0issexubGJMQyIUzWhIU40gWJy3uMrSlGOk1hStOaqqwhqL0BbfVNOmyKkTLRLhJb4aM9i4zHjzEk3/JtI3kVxEgsxio+f2xk0CnnzhMKfvuZ+v/vovc6QrEG6AU54iTSH4j/zm54OHGX/N+GvGX+8Vf30gNz/7NuFvDVNZ4EEN3MdGrzDd/YqodIhb+mlNMwYLRAcCycRq/uUff5cfPvc6N69vcOv2bWxTI33gxecu8Fv/3r9Hf3eDbuZYPXGM5fk58kLTUYHWgmahOM1woc22G7J7+RnceMLYOBobn7QsK7DCY2oTPSOso6xrhJBkaYZzUS1x53sPRKMpJRVFoliZa7E236GTKryzWOdJtCbVmlaWUqQpiZKUdUM7z0mEw0768TW1IpEpUoBWCpFlpElGECWN3U9VC2QISOFppQlBQOMcuYZcC1IJuQeLxyCQSpFqhUPhm5IsSVAi9h+IEC+3ktHozDpHmKoItNYxwriTUKbRIiIQ7ITdm5e4/urLrB46zNqheTqZxzWW8ahmuSVJ9FSNEMAYS9lIKuOn91u8cQHFNAf8Vtbg9Jf3o4e4JtV02KFnbbnDXBY4/+x3+Z//Z/97rr72KuPeLl6mSFdSGct4XNJZbtPtCsowQMo0DhlEYWtLf2+ALUuqYR+ShHo0oDJjVK6RgMEAsXxgbZwS3Wq1cbWhLiUEiReWIDxSJMgAdW8L6yuawRbelgThptGroKlG9G7dJi0WmF86ytqRJf7W3/5VPvXoYQo3wvuGJM9IVHxGxMzi+W1hxl8z/prx1weDv8LP2TXeNbXXz/r+WyGBO1/jbakops1+TIVucnrhDxrO8ISpz0OkGj9tDgsYL/izbz/H06/scHvHcOv6VWhGaCQEx5VLr/GH//pbXHrlOSb9y3S7czz5pa/y1/7OV1nKV1nKBPO5p7W2TJF+ib3tm4TBOhiLdopC5ZRCYOuazd1tKmORSpOmUWlgjMFP3/MbKWMfHUyRpFqTK8Fyu8XqXIdukWKswTmPAhSCPElIs5TG1LTSDG88dV1RyDjrpvEOITy1tTSNQylJnmg6MgcZGIyiqVcmQQiPVoo0qPgzRcrSfJvd4ZhmWBKUYGQ9TkqUlhAEKjiOLnZpJeCNxEwloNJPHzmxnwaPDqkh+APC3E8bK6WQSmIN+HLI5sWX2L3vMS5cW2R5PsE2lmp3l7V7lrC2RsnA0dUFtvcGmOAZTJpIHJK4+xfx8f9F6ug/vVYFd0bd0Tdi33reec9v/M6v8+2nn+X1C6/yS08+yfzcMtdu3GT31hXy4Mi6hwgyzu7JOhpkGmfRmJqmrFFJgjVjqsEujQRjS2RWkCYdcBVGOIwdI43DTHp4C7GDokYEi/AGaBBKIGWOIOCqHfBRUlvLJL5zoZGqjRYpBEfRbXHy3En+2m99li8+fpKubgguUGQFWiv2HWZ/HnF8WDHjrxl/zfhrxl/wAc38vH1I4u2O0jlCAsKDMPEiqpRJaej1RvQHQ8rxGCkFC0sLpJ0ljp65n0ebBV7+8e9iJrsob0CmIDzj3gY3Lv6QcvsaTblOrxxx5fUbXL2+yX1rc8wnOUIGiiKh17TIjz/A6OZlUlczaRpqD2MHG3tDtvZGULTx3hII06jFYa35S8Zogam7pghIFeWgiRDgXFRACEEqFZnWJCqmg2NzYUW/rPChSyoVIlhq51Am59JGj9dubpGnmmOLGfcfXyFJFWmeU5aGvPCkKnbKaylJlSZPE+Y6bZYW5hnWjsYYEqVwAYyPvg5rcwXHV+bIhKORgkRrKhcJTgg5/YrqCSnjot6Xxt7ZJCoQeKFRSc5g9zYvfu8brF+/yvLKKsVCm8UWEBYptGauSMiSFO8MWzs9xuPx3ZES/6W/vPFPIRUuBB584F7+L//n/yP/+B/9E1585jt85ou/wqkHH+SZHz5LM7Ek6Rz9/pBUBQwBOY0gy0mfyXDIpBpSjfpYM0EnMSpL0pwkTRjvbtOM+wgTpxQ3dXS0VRLA4F11QI7S5wgp8L6KX6FGkpCIlETPI9MOIutA0kK2Cx545DR/63d+lUfPrdLVNakKhCSbDge8g0Q/enufDzhm/AUz/prx13vDX+/65ue9G963v9Pbr3Z6QOCFogmSK1d3+dqf/Tuef/4ldvcGBDRNbXDekxcZy0uLCJVw4cJFyuEA6RssCp21sD4O6mvWr6DdOBpRaYnOcpqqoUg1CPBCUjeWYSWx6SpBzyHsBkolWO+5eusWr129Rd5doJGKcjiOyW3n4wTk6WTgN5rnpjt+JRB4lBSRHp3DBYuQAokkkZJESLSUNM7ippbsW6Xh1fUbPHL6OKvtlP5gyMT1+dqPXuby9ojaC9rS88TpFX7jiYfIE8WkqWm7gkTKGJEJQSolmdKkUtLNcxY6bcr+gDoEZJBYD6qpOXvqKF0Nife4aaMggHMeKRQSYj1Z/mSaWKkoG3XOYYxhvtVGkmOExpQ7XP/xn7H1+hqduaMsnb6HJz/1AO1MkwjDQq4ZN5ZWFmcKNU0Tr9m7WLEJYdrX4C2f/8zjPP7A/5NXL17g8rVbXN6p6BQJNumws92nHm+DipOHXaLwTUNoGnxdMikHlP1dgq3wPiHognanixKBwc4Gruoj8HjnsPWQ4JvoFxIsBDed05QhpARv8KLB+SZO4NYpSWsZ1VojmVshn5uj021x7uwaf+M3v8j9Jxbpyppchvj7UoAP0yz72ynbfDQx468Zf83466PJXx+xzI+Y1sgBLEFKmpDxoxeu8T/+/l/wg+9/D+FqsiQlLVJIFkhac4zrhnrHUI82kc6ihAeVkKQddNFlZWGOrfVblKM9TDPBBkF3cY21I4c5fXQVjcM7CCrl5u6YFy9swNhRkVK5wEQmXN/d4tLVayR5i3a3jQ6SsL2NdZY8TXBTk6x9AvmJFDrA9HtNU9NoidRRWaCTBBkCSkTzrcYYauPYGIz5i+fOszmsuXJ7g19+7F6oa1yQPHbvKY4fLdnsTZiUDXvDmtev3WZ1rqAWCr+/iBBoKUiUIhGCXCnaacJ8K2dQVkzKJjarSWglkkNzOamIEsP9fr0gYr0WH6btewGmKhDnPGmaAuBcfBiUkrRSTUJBvwpgx6Shwg9L+pMeUnlWvvQobR0QU+WI845EvbHgw7vcqCuEIPgQxwGEmvlOyicff5Cl5SXCsy/xTLNLu3uU3vaQ0GyztbvN4tIhjC3peYdEUg33GA22sfUQgkMXXebWTpEmit7WTarxDtKWSBmnYeNLRLDg1PTOSJRg2g/g8NNCSQiSNGmjswVka5Vi7QRHz5zms595hEfOHOHYSsbyXI5wFaYJZDqNRnHhDeI4eI+zDdB7jBl/zfhrxl/vFX+9L1L3d/oab/o7Yf8Psf9DWBIu3djj333vZW5v7sYUrK3oD7fwSIq5ZU4uL1F05ynHJXl3gfFwGyZ99ra38MZTDQcIbzh+5AgXL+7ifEAmLc4+8kk+8+TjnD22QlVOEF7TVI7vPvcqz7xwhdNrbZbnVim329zc2OTlK1fReUZ3rkO306EajEAEEq3RSiOwBynVOw2z9qMnEQTOB+rGUCcKiUIrSGGaggXvPHXTMG4M/WGJ9YKiU9Cab7O1t0fqY3Pk0lyHe88cIc0yNnoTrty4zdZowqQqOX70KIlK0FLF1ksRewwSFWvneaIotKSdpQwaTxICKk04vthlochROJog8SLWyR37rZshqkKsI7pnKKyNRKm1PvAFSZMUrQIqVWwNx9NroHDOE2gQrmahW6BkQEyVHamSJCpOYka8oTZ5J+vq5z84ASHiuxPTGB2ZcOjoSe7tlzx4/728cOkmRSHoNWPSNEFmiv7ODcY7OxR5TlX1MOUAEaKpWbAK4QyTwS69rRsEM8B7Q3ABgovrg0jEgjgNW6Aid+AQUiFlRhAJSWsJ3V7i+NmzfOrJT/HoQ2d5/L5jdKlQMlA5i7FgpKQQCr3/fn86Rf6eZT3eH8z4a8ZfM/76+PLXRyzzE9PF0asgZbfv+IvvPs/3n3mO/tYtnBkSzBBvR3jnqfYqrr9S01k8RkBTSk3e6dLqztPurNDfug1YqnLI+npNa36BnhmTF3O0l1Y4e/oIRSKwQTMsa4bViN3hkOF4yNX1Mb6dsrUx5NaV1wHB3Pwi8wvzdObnuXD9FlIlBASVcRjnfkI9sG9aRfDRZlzEOTZxyF5MW8uDmxtw1uK8o2xqRpOKVAsOzRek7TYd5cHUJHmbPMuYnytY6HbIkhThwC52KOuSlaVFlhcXESESUfAeLxRuOtVXEVPIeppS1kqSSw1K0EokmYIQRDTyClMjsKmaIZ5m/IsPDi01RVEc1MvvtMdPRRob1mwJIUaxIUiU1rTn5/BJQuMhQyBjVp1Ea/IsR8pwMJfm3Vtl+2styot9EGzujfnvfvdf8uPnX0BlObu722zdvIUZT1g9dgKrcoL1KFEzHvUxpo90HoEGFL6eUI0GNMbRjHdRocaFWPq4U3UVo2iPEB72lUAIkqRNVizh0Ii0w/LR4/zO7/wKn//0fay2FZls8D4wrB1jJ9gblcwVipXFgkCDR0ynMM3w/mHGXzP+mvHXe8VfH77Nj4A3BGx39MBPVRLCNwgBI6f4zo/O80d/9G8oxz12br+OsxZFIMEj8Zh6TPBgyzE6KfAKetseJTvkeQcXJmgRUEqTZDkrC3OMxhWH7/8EtdCYumIy8Qgp0CIOwR3vbHH7ynn63S5yKWW3N8QLyeryMkWnxdLqCqtHTkBnnj/7xl8QvCeIqBLYd0fdT6FqrXE21vW9AucD1nuM91gf0C5grMdKh9AS4z21DwxLw85gjHOO3FtW5tocWV6kVcRpwWkqaAhUVYWXgcOHoqmXllEZ4l3AiThcz+OiiZiPNfsskeRakClJIhUyCLJEs9zpTNs1p94ZIXrNxlSkjA+0EAgRI548K0izjMGwjydQFJ04T6euaS0uMqgagos9D1JEuWnWmmP55D30jKRXS1bSONdHCEjk9LWl2Hf7n9bOxV+KCN75GhQQ3nAm3Rs7/vnv/QkmaL7wxc+zsVdx4eIVqv4GzkuS9iLeSYpiAVv3CL46iEoJkQS8tdSTAcrUCFtPU/fRGIzg4vvwMeYMxONKoVEEfFAUc8fIl47jpaDVyXnyycf55MPnWCokSbA0TjBoPFsjx9awYfP2DX7lU+fQUhJCgsL+ROJhhncJM/6a8deMvz4Q/PWuDTZ9p7/zs15jX8S2vyh+cnBZQMoUK+Dq+ohnXr3CrY3bdJXlt3/nr3P4xBme/t5TXHrpWUI9Am+omyHOlsg6wYWGphkjQ5tR2sL4Ed12l1ZriXJiCbZmYX6VE2cfQuiUm69fZ/WBk1HJIB2XLl/ha3/8RwSRoZTAtjPSLKG9uEir06G7tMThEyf4ld/4HSbWc/61K9y+fYu6mkyVEm9IJt8wCgPrPDLRhOCwwWOn5OF8wE9li9KDDQGV5KwdmseqXYKQLHULFrptuu02WkisNTSVxzZjdJLgQ3RKDc4jBTgn8V7jvUIphZ96UFjj8cGjFOSJIks1srR4E5v0gosRkuUOqauYNqJNv5QSCAtaJUihYmQWfJwGHRTSOQotaC90uPrarXhvpYyzenTB6tF7OHrufq7vjule3+bTpxfReITSeF+RaEmSTqcfv8Oy+c+UPsO+hhQhJI0P/PD5Fzl67CSrS3MoaXnx336fqor9CyunHiBbOITZG4JIqOoRAoPwkhAs4PEolNJoBU01ILg6mpJJBTIj4CEYwEyjz0AQAh+imkW3l1g9+yBHj53g5OljLB9e4Z7TR8mLhLqxeAljY9mbNPRqzYsXrnKkKzmy2EEFhztwlP3oY8ZfM/6a8Rcz/uJDmPkRME2jhbh7FW9s94Tw+KCovebC5VdpzIR/+B//+3zh059i4fAJbmxXXN00vPzqRfykTyqJDyQOFRzCh+n8FYNKJNa3EUmXrNWhqkcMRzsU84r+zi2kTLiajTlzfJ7SWtIk5ev/7tvU1nDixDFWVpZYkGPqdk42pyjmFjj30KN88Vd/ndXDR7h2Y52mqaNc1Dv2V+Q+aXjv41yc4GmMQXcKnPUY6zHW0SiPFh7nPc4JpIhE0m61QLcQUtBJoZUqskxjrKW2DmscwQXSLEUnOULJaZTj8M5TBocLHusVqdIIoQg+Kh6MtSAgyTRpniJHDd4YEAp0gvUxTWy9iDt/H70lAgKEREmFEgGlFQEX6/9VjU4SnKvRWqPShM1hzcgEQnAkqCgbbS1y+uFPM7eywnqvz6s3Nzk6rzg6lx70S3TbBe0sppLfwBsfNHdr/eFj0yNC0+/3WFqY48haC43h5cvrXLh8i9pnLJ94hMNnH2E4NgQkTVND8ITgDs45zt3JUGkbrRVNYwhYkCJOSk7b8ajB4MyEYGs80cxNEPC6YPH4fdz32KP8xucf5cihZa73G8rG0huViEKhlWTcCIxP2djpM9rb5rOf/Ry5ZlqLl3ghp/OhZng3MeOvGX/N+OuDwV8fms3PG9p9gZ+e9n7N+MACKoQYfRjDo+dO8sUnP8lcK0UFycgJmpDyxS9/GUnNn//BP8NVIwI2tnzFYiROpMi5VQ6f/SR5dxlTW0a7t7FhiKeiHK1z/pmvo7Mun3nk71A7waRRXLpyk+u3tnjs8Ud5+P57WOzk9F9/mcGoy9x8lye+8CUe/fRnyFrdeMZS0tQNraKgqSpCiF4S+7XyO+vnxlqE1ITQYH2gcZD6gAkB6wM2xFSs0hlJmmODoEgTspVlWlkKzuAaiw0CkaZIFFmnjUoTwCOlwQuDcw0+WBofa+bGNWiZxuviPc5H+3OITYRCxiYzGwLDSYntdlE+4F1Moccccqz3CxlTx1pGLw/nHI2xKBWb3qQSOO/wImVjt8Q6jRIBiSDIlNVTZ1g7fYpOp2DOe+pxj96o5uRCjgiOVpbQbiDP5NRqfv9D5l1IG8ePMJzz1GXDfLuN9456UnFza0B34TDHTigWVxaZkJO6IaYqyYqMZgLsD/QTMTLS2RJ5ew5TjwiuiZkBlaKSDjrpgpDTyElgvSV4iwwBrRNEe5UHHvskX/qlT3LiWJet3T472zXtvMBnGhsUtZfsTioGwwnrt6/x6QdPcvboArGVUyGDxx9kIGYKr3cDM/6a8deMvz5Y/PWB3/wcpIv3HyYRQApE2E8hx7mt0RosIYgcncKp4wsoqWNqFci1Z2Ve8sD9J2i3/waj/i5Pf+PfklLRNDVSZ0Accnfi/ie5/5NfYXntEDeuXuHqKw0bO5fIBPimpBxtsXzyAZAZtU25ffsWL774IveeO8mD951gbb4DTUmTeh758pd57NNPMrdyCPabAIGbN28glUQYQZqklFX1k+8TpmZaksbYqeunprGeyjjSBNIgaHxAh0igEjH1mrAIJUlUSn80wdTNlGAleZ4ShMSUDalxaCVJhSRNCnSSUjWjGLX5gCXgptJGF2L01Ewlns7HCM4HcEGw1xtgl1toNZ2ULAJKSBAyOopO/TC09Dg8zpn42kodyBKlTJCqYFJZHA4lJVZIZN7l5NlzLC7PM19ofGixXY8wLu70tfexYTGBVp5MSUOB2HfG3a803601CUjJqKyorKBxMByP6PcHDEpDVTc4ByopEE6DDzSmQWqNDwIl1DT9K5G6xeLacdIkZfvmHjgLQaDTFknaRegC5wGhEdqhfIM0Ps5MkgUrR8/wq7/8eR48ucxef4/Xbu5gQ8raYpd2keCFYKc/YXNngLeGB88c4nMPnyTVjuitK9DBIN95pn2GN8GMv2b8NeMvPpD8ddc2P++FbHTfyl0SCELh0RgvGFfTCb6tLrUTOKkQVoKH0lgGo4q1pQKdCaTwWJlx6v5PceHHzzDauk6SHiZtzWPKAVkiac0foTaWutnD+zHluI8MEqVaJIVmUlrStIVO57l2fZ2v/ckfcd89azz5iftoZwLhDYeOrfArn/u7tDsdvMyJE1vie2jqkq/92Z9QjkZ0ul2ssWR1g7HR/FspdWCiJYXAWIfzAa2iw2ZjHY0LNC6glUM5CTLSp2scCI0zjtFkjLWORKeIEJACGutjWjIEyDMCUDZNdFlNBFom2NDg9qNQMZ0JHAJ+GlHFVLWPDYzW0eAwOhqlxaF4oKQgKAlGYL3Hi+k8HkyMDrWcPijxPnkC6ATjJLV1kLYQaYFKWqwcOcn9D9zH2kJOmihG4zF5ltGb1FRBkIpAoqGdaYpUT2Wcb7627o53TcAEz/XdEVfWJwxGE7ybEGwgyXKEt5STEf3dHbzMwEzwziKTFKESsBYhwaNIi3m6i6tU4z7eNUgXJ2ULoRAyAZWh8wIpBE0pwdV4ZxEoKJb59BNP8NgDJzGTPsZGGfNkOEIqS5JIqrqhLCuUCNxzfI0TqwWLxXTisSA2LPKGqR539Tp9eDDjrxl/zfjr48Vf72rmJxz8GSMdgAO1QxB3/F8OmrAOauAhNkUFBN6DtYHaGEalZ6dv6I1qKq/ojWu2BxOOHjvG5x7ICAJGXtLrO8ajmnFTUTaOCzeGzHUk6IxrN3e4cm0d7y2TZsLRh75A0T3GZPc6u1u3KCtLp6UQZkgzHjAajkiyNu2FeURaYNIWnfl5nn/+WW7fukbGiCcf+wJtKVDW0erknD5ziqKV4YTEC4EOHoHHhcCff/1rfO1rf0ZdV9z/wAOcH44QUqK1RkqJtTGdChyQyKSsaHfb0PjYxOc8xnkaC1o4EIJgLdYLhLCUVRlr7VITfBQCKilwdUmiJI1paLzBJRprPUYphqOKTiop2jk+RGWGlx45Tf+GaRo2CEUQEqUSlI6LSIj9ZCooSWyIm84gctMcshTT23tHdKiEjFFNEGido9J52vkiKu/ihWL10FEee/xhHn3wPtodzaj2FBNF0HMMBjtsjWsOdRXBOxIlSRP1UzXzu7iYY7iO+P+z999Plib3eS/4yczXHn/qlK+uau+me7yFH4EEQSuRlEReSitdKRQbYlzF3Q3Fxt6I/Q8UsT/sP7AbG9rYuHf3XmlJORoRdCAJcAbAYAYz7V11l7fHvz4z94f3VM/AEg0CmgFQ34ia6a7u6qqTb+Zz8mue5xGQZIK3bu/yzt0+w3FEPTD4tiCOhwS+g7Ca/e0NCguhqyiKFMfzUW4ApsBaA46PE9QQrkN/sA86BZsjhIvRGqEkKgipthcQ0qG/pynyMcIKXC/kzNMv8fM/9xmqgWF3kIJ1CZxyH6UFjJMcRwiqvsts0+dEWzIVWrzJnIS0BcLqD/hJcdSAOQ6O8esYv47x6ycZv37kbS872TDSqnKTSDuRSyjllaR00BqkNQhZ3tCFkAgU41xwc3Wbe4/2SbRDjiSXPlEq2NrsMuwPQQo6cx1aiz43d5LygFhJlML69j79UUyeajYfPWJrYxWbJ3jS5f6t6wy2t0nH+zSbkpXnX0Qkp/nr//xfabU6WKW5e/8Raw+2qLYWcGhy/vJpojyjHS+x9eAeu1tfwnUMv/D519FAbg3GFJxcXqJWqR5dQlHWTMAQtC54+513iMalANb9e3coshijCxAC13Ufm+WV5ddSLn40GjHfbpVqmdaSF5AUBkeBtoY0zclM6b9S5DHjPMdRDo6xONpQURJVaLIiI7MaC6QTeXxjDK7nYawliTV1bXE8WdJFtcHDRRg7cRouD3tuBVaJiV6DRSkPTzk45GW2JyzWSKwtBcGUEDhoAldhHIextlgt0GS4rofRoNwatYWnMNVFwmaHJB6zON/kxWfPszxTQyiLIaEdKqoq4EHisNqNCZ0a0lqSLMeYIz+kCZPGaj7wFvV9h3gMhbzPUAAQljzLuXH3gDfeWWO7m2PyEVtRH52MsTql0NCYarO3vUmaJthC4QiDkj5h8wQ6HoA1OLUpVLWNEJANu1iTTsTVDBJdtjuqFeqLK2h8kjxF6xxj4eT5i/y9v/8LXD1/giIZ4no+VlsaNRfhT9GouAhbELiSSlPRCB1CT6KULIHr6HxOeuXHo87fOY7x6xi/jvHrJxO/fuRUd2FL9QQtc6AEDkcGiMJiZEEuYFyANqVZnFKKwgge7fX42rur7PdTFhcWOHVyDtcR2EqVWxt9Hm0P2OuNEEJivJCvfP0WlWaI73rUq1VazRZ4NQpbUG+1eLrTYrbT4OtvvMHm/h5XnnuJd4YPyAea/Uc3ee7n/gFz08+SjFLkVIdKTZHGCa1mm97hIZ25eRzHYe/hKkHYptAOzfYcZ04vEOeGO/cfMdXw+eQrzzM3O/v+OtlJeW4CAnu7e9y4caPMlJTi8uVL3Lh+g/b0NOvrG99mkqe1xhpDmmcUxuA5DhiNBrJCkyvIJwc4M2ClQec5RWGQxmCwjNMM6/t0OlO0plqMspQgrCAdh0FvwMaDh4yGMUJAnKfsDyOCqodVlmatQt2VCKvRRlNYi7ECLHiOwpMCXRgqvo88Mv8DsJOs11oMJegIIfA8l3FekMUpZdoVlDMQxqKCOgsXrnLh6Rep1Op40hDoARdOz1PzBUmREyrLfKtKrB2GrQ5r65uoxNJu1jgYjAiDEIN6/0iIbwaO73v/2qP/2Pe/XAjiNGNz65DrtzdYW93AWknS36W7t4WjBEYXKD/g/PlThF7B6v0HkBcgJK3ZJaQKSN0qbuBSmZojs5Io6qLzeAJ0lL1+UX5f7VQIOrNoC0v1qwwPZ3Edl9c//Soff/UynswQsqAelM/fSJc6LjPNClLn+LKk9noKHFWq0b6/Iu+Xib91VX5S1Z2P8esYv47x6xi/4Edc+REWhC19UgpZUtsUAmsKrFTcedDnz968wcD6+PUWrXaD0HcJPEmjEnDu0lXOSY9mw8cVGg+Hbm5RjoNfDegszFAYQbUzg+s5xEnMoDfkcG9Avx0zMzdLmqdE+yPOn5zjZ19/mY8/d4aNnS5Il3vv/RXx/g7bj9Y53LjOy0/9PU78/Z/l6w+2Ca0h8EIOdnbwfJ9Gq8n62kMGBwdEckSjWuHK5XPcuvEWW2uaZ5++wC9+9pe4cO40wr6f+XzTegjB7u4u+/v71Gs1/vW//td87GMf4z/+x//IOEr4wz/8Q+7du/f47z/uWypJpjVZkeN6LjBRTLWQFZAJi7WGZKKfYYwplU/zlARLpVElWJzj7IvP0ZiZJk00IGk2myTjmD/+vT8k6g7o7+/TPxgQ1CsMswykwXc9KspFlJ12yuJ3aVAYCEHLc5FGM91sTHr9+WR401KgMRNmSGFyRnGMcrxSylxZHAdwXJTRWMcjaM9w8colXnnlaRxp8cjw8jrtmkRJS55rmoECXLrjnKrrMI4sf3rjBjMzUyjH0qoECByENUc1auwP0sw5amNMwMMiiNOcja0D7qz3eevGQ3p7u+SjAdnwkELnaNdHeR7tZp1Ll85RCy/yH/pd+t0IaRW4Pn61SZxoqu1pnGqD0PPYuL0GtigLt8LB4pRKa0WGIyWXT81Sb7g0W1Ns7/VpVFw+/dxp5qsWmQFWUlcFiVIYI8BqfJsQ+A6eAIlBWIMj3Ykw2U/XPM8PGsf4dYxfx/j1k4tfP9q2l4BSwVIirVO+CAy5Fvz//ssf8z//h7+ivXyRc8+8hF9tUZ9qMt+uMt0IEEVJVcQVaDSj2NLtjjkYJXSHEbValXarjrYwzizDwYjtuw9I+n0Elqm5Dnkypj3TYnFuhtmKS6diODXV5sr5WUax4cHnf5E/yCVRtM/OgweYKKK5MEWnXmU4jAmbU8jtQxqtOpVahfGhRJmcdDRgZeEEz12aZa5ynouXzvOpT7zKdLuOpBz4emxSZ+1jEDnqK2dZxuuvv87P/dzP4fs+/+yf/3OyrGAwGLC2tgaTv5PnedlznmhjpHlB6JUbwIpSPbTQkKnye+TGEmcFAiiilDxOmFuYY/nsGRwlcYxARTl7716nSDIOPY8sSumkOVWg1axzslVFhgGJtETJmIrrgrZobMmYsBOCoQQPy1QY4NiCigKsnsill3oZZnJHl8ohyxMKA8vLyzzYWMcKgS5yhAYtXPzpRZ568RO89OwVpusOmAxVZOUQoCsxRlP1/ZKloXOkyEmSMbrQ7GzusLe9TaNZ4fkz06gJS8JOpNN/kLC2fHZyMtCRFZadgxFbBxHv3llnNI7pbd3H1QUSaDTbeM0ppO/Qmm7iVQLa7RoLy8uMkg0ajRYoRW7A8UPCZptMQL3ZAKvLTE94COUhhIuUPrqw+MJwebHOxfOz5E6IKwynF1qcmoKAmEhbChyUYxFGIRTUHUvogOdY0BopLFIKKoHPk3MiforjGL+O8esYv35i8etHdvkpD0z5gxpboKQEK4hyxb/9//wh//733uTMSx9j7vQFZL2OV6swv9BhtioZDSM29hPqFZc0HvNwfY/VzT4yCFhcWqTVaLC8NI+noDCa3YOYTSMYVSsk/T7GWAaHfcJKSDTsURWaVz52gZYnUCYncCz1uuJXf+VncepTvPG1N9k76PHWzVX87UNmO/PkFcmZixcpshzHhbm5KfYfZsTDPZYXpvnX/+of8+zTl5Fm4mI8mQE46rSKCS30m83m4Nq1a/iex6/83b+L7/sw+Vrf9/nt3/5tNjc3+drXvobjOPT7/bJsDPhBgJiwKMRkyM4CuYUkKyfjszxnHKeYwuBZiyMENeWiBjEhkt5XbzACVBbhGoOrHOquR70SYOoVcluQmYKRLejGEU7FRzIZHLSawjzWp8V1FJ4ShL7LbH2aVuCALfu8ZYm49MCxk1XJCk1YrTE9P8+d9Q1y4WK0wXVcppYvceKZz3D2yosszbapuqUvj7WlYqrAIkXZd5bCYqQlCD2EgN31Rwx31smziHSqiWOfQVBM3rg+qPz5Ax4aISm0Ye9wyKOdPtfu7xKllu7WA9KDB1jHQwVNdJoShiEXnz5Pox5SaM32zh7Vap16s4HjusRRXJIzBTTbDbx6jfGgjy40QlWRjkS4FZRXASEIGm3OXLpMWKngez5RkjPdqjLXrhC4kjS29KKM9cOEdr3B/iDi/uYOn3z6FG1PTcTnDFKWFGEpSkj9TiXhnzZ2198Ux/h1jF/H+PWTjV8/4oHnsm/qKIG2hsT6/MXb99lNa/z8P/yn6OY0W/s94lHG7Nwsa/spb761xq2bdwhDH6VzHt5dJc4lYWOKZqdNtx8T1hu0Gk3adR+tM6xwmW7XGC7OIH2HLEqJh2MELrtbh4y7Pa6ebRPOTqG0QZgcKQwrs1U+95mXiK3lT3/vj3jrza8SG8Fcp8Pi2dNQZIQ1n06rgu9oKEZ84rUr/Kt/+d9z9sxJ1JHAmFWPmR32e1zU796+w3/4nd/lF37+F3jm6acf9yvLKXxBq9XiX/yLf8HNmzfJsow0TdHGYLUhjhMODg6ozM6Umwxbak9ISa416NJ7WEmFVJK5ZoOVdoezC0sEQqCSDM8KHM8hrfgYOym/ByHNSsjhcEAyHhJFKYnJkKqUYrPGUBRFqXiqLUiJkAKlHDwlCZRluuZT9xVKGAorHg+hCQRWlDMTWVGQmZydvT1GUYQbVJCuwUqfladf4uzzr3Hm1DJTocQXpZJroUrzQWvLNyIFJXgIgScdRodDDrd3MFGPeNyl1akThMFEUr7MmR6b6j1hAiUmPz8WRlHKwSDm3toBD3cjDva75PHEZFI0KApL1QtYPnOGkytLVMKA9UdrjHpd4hxAkUYxJtckcYqQFt9TLC7N89bqKsIqZNDC9SqISgvh+DTaTV75+Cc4dekSxlEc9CO0FZxaaNGulJTdwrggBXc3d/jKG39OmllWzp9ndEmizUQ4TjooJXAc9wOl8OP4/uIYvz4Yx/h1jF8/Sfj1Q7z8fMCuT7z/O4GkMJAS8M79Hg+6ghf+zs/gV3we7A3Y6u9Tq9fodfus3tihf9Bnf6dP/+Ah0lim55YQoUeuLb3dAfXONG6jxt2H+0iT4YiMdqvGwsIMCwtTdDpTHOwe0j3oMkoSXM8nNwV313rU/YCGL3E8n9BRSKNZnq7w4tNXuPbG19m48Q6uH9C9D8PDPeYW56jVfTpNn5W24vP/+re5fH6RwLUT+qWY0EHK1/1B4PhOe3Vza5Pz58/zz/75P0M5zjfxZIUohyUvXrzIpUuX+PKXv4wxhsAPiJMEWxiM1qRphsJFSYkVYpJNSXJTIKWkVvGohnUaSuJai40j/CBAeYrMFOSewbMKKR1QkkIYRqMBvWGfURITF5pUZyhpcI96zqJUQT06h1IKPEeROxJPSaQpSuqvlVhjS6EyU5ZtpbAIWdJFR1HMO994j1xIwkIjlaQ6M8/5K89y8dIZLq60aQWCItNkeYJzBMhSgDnSddBlWTyzbK/vEg8jpJL4YUirM4VfCdFWfIADYB6D2ZOGEKXGxzBK2e8nbO6PiFLBo/Vd0nGCBYzyqUwtMHfyPGGzRa87ZDAYM4gLemNNt58ghEuWjHGdUiMj1Tk7u7uEzSbb23sgfFTYpDK9QHN+hZmZadrNCqfOn6bq5ix2WjSrAVme0/IK6o5F6gKpDUrkSFdy58Eqw36MDCrcvuOz8uLpciZBlrorAjmR6//JHGT+28cxfh3j1zF+/TTh1w/l8nM0b20n5cyj8qmldKpNrcO1jYivrg4ZERBt72OygqlmnVNzHTY299jrDjhYXaW7tUahU178xMd47sVnqXWm2dga8qe//8dsr93HZAk6S+mN+nhBiMgK9lbXGR72eOmV50EFFBq8Wp1Br49JxwSuT0rI9iChMlMlcB08p1Tt9ArLXKfOzOIKq9feJtm9i5HwsP+IlvdJlpdeZrpm+eVPXqXmeyBzQD0uC78vyvDdr6RiwpQ4f+EiJ0+dplprTLKBbwYZay1BEHDhwgXeeOONUiRMKjzHodWe5qnzF+nt7KLzGMf3S789JdG46EzjChBWUxQ5CQ69JKIyFMiighKCWBcUsUBYizvxvcmMISpS+vGIxBRYaXHRiElmZaQEXR5c6YAVJevBmRgEOlIghESbEiAMktwaNKWFjEFibKnpkerS1cVxfYyR1GZWeO1nfo2LF59ioenRDEs2Qp5kaANWSqyVj+mTalIK1zjs9kf0hxFCKhozS4xGI9ygiqaUXheiLLeXy2z5nintd3xoFmMNaZYTF4b1g4itgxFJnJEMY6JxghAW1/XwwiZpAXs7+zjTDSrVgDQtGPYikmGMySKybEycWChyvEqDar1DqznFwomTbK+7eCLnuU9/hnpniufOLXJutopUkkBBo+qQWwO6fLOyQmJNjgFGmSXHYXb5HNZssbuxQzpeQoqSbBonEZX21MSx+rj0853iGL/gGL+O8eunDb/+Vpef9+mQALK8PQvzgQMhSXHZGxYUxuPS+TNExmG/H5FnmkboQlawn+U8enCf1RvX8J2C8xfO4lm49s41Ig272wfsP7xHMRoyVoLB3gbGUVSbM9gCiixmbXWTsFpjduEESkhCz0O1WhR5hfEoYfXRDu3qEtGUJNKSwhp8TxF4gkbFpTE9hfUC0nSMzXsU0R7dnWWK5AIzUwuEvjPRhPiApsC3siE+8N9vWh9KqfeFhYVS+0LKktHwATrp0ZdJKfnlX/5l/uAP/oA8zymKAk85jMcZ+4djPCdEiAIhNVKWHWrP90l06ZkC5bAhAjJjyPsFvSgidD00gqQoiHSGtRZtDVmWo9EYq3EcST1w8TwH15GTv2PLwT8BRyKaWFBK4nkuSogJDbY0MzRAYQUFkBuLFoIkz8mKnELnKM+jUa9Sac7xyus/z7Mvvkqj1kDgMi4ctvt96jIn9FxSbTBGlIaDuSYUEiEVibHsD2OCVov24gKehCBOac3M4Lo+E6H877xXPxDfq088kcYgSVJ0YUjiHK0tSZSAMdiJwV+edokOH5CMdhms+ey1myg/RKmQIs0Ydfex+Zgij3C9gFGeM9uoce7MIq+9eImTJ+a5dechrtI8++xlhIl56mSNGZ/S+RqBNCmeFQSBj+9JpNEUhWZU5IwyyEyIV5+ns6joVA3nLizTT3OyLEPpAqejEBSTDPI7g+hP4xzQMX4d49cxfv304tcPqe1V3uiEsI97lFYINIp+CuPCp9Gq4BrDeG9Eb3efbq/Lgzimd9gjHqcUuWFx+STR+JDrN+9y69Yj/Hqdzuw8G6v30eMhQa3B1uZDHJHjuoq8v4NSIQiJoE00GhB4Lq2pBnuHhwjHMF2b5sG9R8SpoTfOeLAzIM6gFrh4jkUKQZTDuatPs/5glXd2b4E+RKqSAumaMSdmW0hRCryLyQN4kreFo8HBow9jzDd9/lt/ffr0af7lv/yX/Jt/828YDYdICWkhufdwk069yoVTc+RRH3eioqocF+W42MxQVlgnHjZSYrRmkGWYvEeeFaWyKpbCGuyEVRD6DjXfJ3DdMqt0VSlORina9i2vZvLEBY5ySlO5CZvCmAmLg9IvR1vITQke2hgcR+K6LkWR02h3uPLsC0xNTRH4HmGlxvb+mIPDQy4uNEhxOExipFIkhcYWmqlA4ghJrguU7zO3tIBfrSGx9AZDAqd0Yj56OH+bCqkQkOcaXZSva2Nti/EoYjAYYmwOopwNyNMhyd4dHCdE4dHbrVJpzFGtTVFkY5LxHr4rMHmBcXyQktZUg5Mr87iuYHGhzUynwonpGjUXXOsTeikKgRAuxlgcR+A7CtdxEVJQFJY4t8RpSdpthnDh7Ay9uuGTL1wmTTP2RwW33n2XX/ncpydwYfmgg/hxfDCO8et7xTF+HePXTyJ+/ZAuPxYwk+umASXIjaSfarra495ewrs3brHfH1IYwXCQ0miEKClodGZZONkkjiLS8Yjezjbe1jpZHHFwcIDJcnQ8pFINuPrya9xffcj+o2uMD9fJepsox8evttDFkAfXUhwkF597liRNqNQCzp2fo1n3WV/fJ2y26MYx65vrOI5kc2MLKSRXX3yORrvB3OIynblTZEOHlfPP4ldclmfrnFqY4kheQFg52ZXfH3x88PZ5ZID3rT4t38yosEgpef7556nVauR5huMGFKnFas0gHuJWVhA6QOojaW+B43qkafb4bqyzDCMmIGHKfrsWBitLM0VHOQgpcJWk7rs0g6DMmhyDEuID8Ch4LPMlJXrC7ihdnCdlTATaTqTgLRQICiSZ0WQTLx8mGaNSCmNgZeUkyydWMK6HVopRZtncPKCIB4ilDr3MshdbPE8wji3SWqqupS4N1lqUEtRrAWHolRL6jsAxObVKWB4SwcSCQD5xxbh8JrIED23JM8vDtU2iXBEnCYUG5dTxwnmMjhGmwFOy9L/JY2zcI8oi0uSQPO2ROR5BZZoCj2bb5/VPfZxWq01vlBA4kvmWS8tN8bA4ogANmXTBqnLYT1l8JXFk6YSdpBlJbjDWRdicq2emmWr52LNzrN27T7PR4L3rt3j6whyNuouwBov7fe/Zn744xq/vujLH+HWMXz+h+PVEl5+jm/+3x2SwDIsVFotLYl2GhWCtm7MXpcyuLBCMZhgMIjozZQksz1OkdBmPY3a6PdJxhDASP2zheSGOdEijIa6jOOgectDtcfLMOeLDdfLuNqJIMXnCKBmhoiE6y7lrHA77QyqdNiunV4hHMbbQOK7HvfuPeHj3PjozOMqh3+tz6tRpdncO2Fx7yNa9GwjlcfrSi1y++jxJvM/sVI1a4ALFhBExeaXi+7uDfiehsO/2Zx/83PT0NE899RRvfuUtzl75OHuDnP2NNeKDB/SjnGZQwcTj8uBYi3RchHJKhU4x8avBIIQFCUaAmjSRfeXg+T6O6+K7ioqjqDgS3xFISTn0Z8ryuGRiDDh53caUUHJ0B7diUt60pSqGRpIDKWYCHAaELKmuxlBYyYmlk3z2sz9LrVYndyt0M006zLl2/S4vX1nE91y2BzGDHGwS0+/3qPmCxZpDjiDKCtJclz+FLjC2ZHXUAodG6KOERQsmtgRlJvedHtb3Gp4z1k5cnwVxkrG/34WwhTGgsbhhBS+sE48SwFDorDwJOiUeJmUxwSZYk2CoAhYhJadPn+KpS+copCQqDK4sqPkuUTKmUIpACcBhlGhMUdCoeviug7UlZTcrDKM4wgiXYWYZxAU1lZKMYna39nnv3XfpzMywNF3htRev4IhyxsNaRbkS5v0B17+hLPzdz/uPZxzj1zF+HePXTxd+fa/4oVR+PpAbYFEMY8PQKA4SxUGs8Ro1djd2yCLNiYVpojRja7fPOM3JkyH9/UN0oZGi3ByFkBRZUfanrcQPasx4Hmt3rrG3Wcd3HTw/wBYCY3KEzhD5AJNVyZMhG/du0I6WsFlGf28fx60yinMWZptMVdq8e/0tfE+CLdgxGbe+8uf0Nu8Rj7vU6w0erj7gvW98jddff40T86/jYLFWYCQTxddJQ/VH1EIwxlCr1fit3/otzl+6SmXxKf7izVvsbg9A1nm4vssLT50miUcYW7oTe76PcktDuUnagECgECj0hI3hoJSkHlaohBWCMCjXUgmk0Wido02B0ebxU5WTDSSlILcCo803l5ItFJPDa0VJlc0F5KYEjyRNGQ5HaG0QUuG6Ab/693+TC5cuUm3V6RUe+9GQhw/WGXa7nFq4iisN0nEZJkOUtviez1QzwFMwLgy7w4RhatjvjsjGEY4XIKxkplWlFjhY9IQjIR7PcTzp47LGUOhScXYYxSRphiEFqfAqAY7RREmXIuuisBSm9ApSQmO0mDBFDMKWbBGrM5SJuXL1EtWqT5omCGUIPUVWaPa7EfWKT7viYrVgu59RWAuej8gFGpcig1GSEmuJttCNDIPcod+NuH1vjffeeIuN1Vu8+omX+Nyvf4KKkqVBo1CTF3/0cRwfjGP8+uHGMX4d49ePA3490eXnKGt4/O3t+9oQVhiMVRwmhru7Y0YGkiLkzt1tkqIgjcbkWU6syyG03nBMYiQUhnqziasUw8GAIssYxSl2HGPSUlQpTwryZIwShkF3G60jlC2wAqSjUEpjTUY6OsB1fZygQn89JVAw6A8xoqQPPrp9kxoSz1r08JDxcIfDtRRZJFSkwQk8kiQiS2NqvmS26bE02ypLpPLI2fkIOH50IaVEa81rr73GS6+8ypu3HnHt7jZuWGGEYe/gkNycQvoKnWgwBVIESMclFynSlpmdLa/vKKkIVGkM57uqlOD3Fb4rcR2B5zgIHIxxyXVBnuWkthwqFFKgBFhtKHQ5PKjtB+fuy6l8M/mdNuXAYKYh1RarcyrVgDyGNM+5cOkKV5/7GE5QRyqFLAQml9y6dp0zJzo0aj5SQpYVxKmm5rtMVx2mKxLfsYxSyyA2jMYpN965AcqhMz/NybkGK50qoasmg3F2wpY4AsK/+dAclfTLLMVSaIMpNL1xQpoV+J4mbDVwRgKbFFhrcRBIa8t10BptM44OqaVUh0VYsixmqu5z8tQiveEA31O4GJqhD6YgSUo1XD8IGcYZW70YGVZxEsm4sISBZDQc4AeKwkoOumP2xxb8CtGgz6PVh6xvPGS60+QTLz/N8lxzIjevJu0c/T1f+09DHOPX+6vwo4xj/DrGrx8H/HrCyk85YCZs+UM91sUwBQbLYQQPh4qHA5/d/piDgy3S1NDt9smzhEarSaElYRAQqpR4OCAZjxllGa7jkSYZ0oCvXEbxiCTqInQGWpMnI6yOsUUfnY+QSmIojeiULPMDa3uMihyv0iTVFqymtXAeKzVG54wON9jv9yiiGMdGmLgLOiNJByTWQlDHDwIwHtPtDq+9+CxTjRDHcdBaM2kR8wM4rXzXONqs3xpSltoOrhKcnZ3i9IlZbiwukib7pD2Pe2tdrp7tMMx3S5dba8BxSnqlzhGUFE4wCAmuI/EdRUVJXAHKaESRY63BIHCUQglZGjSWZEv0Ue9ZCqQpj0M5FWF5nDwiMZPMUltBhqCwisyUiqqOIxn1IsaFRSqf5csvsK+rjAYSOYoZR5rbtx+i4yGXnnqeVPoUWhBnEaYwyMAy1/SY9gzKGhJZlq7X793jcH0Tp9Xm3KVlljsBnaB0abZIpCnX1IgfDOgLY0qBM6kY5+Vg3rh3QNhpoa1BSRfHr6Lj3uQrLBJdvqEKQJhJ1lkCksbysz/3WZYWpjEC4jjFl+ChsVLQbDSIC83u2LDbi1nfH+CEmn6U4zs+wgzx9JCr5xcQhcZ3PaRjGAwi7t94wKO7D2g0Krzw0hWeOreMJzl6QN91cPJ7lYV/Mplex/h1jF/H+HWMX2U82cwPIK3hSAnDCoG0BQbJ+kBzdy/j+uqQnf0RtXaTzlybpBD0RhHNapV6rU7Fr9I7GLHx8IAoHpBFY3SWEwYh0WhInowgi8ijLlF/D0yCsjmYlDTpY4sYQV4eZKMQSqGVQggHKS02TVHSYo1ib2Md6bbw/QbJuE88PkBicD3Ixwkmi9FZXGZ9ZGTDAbZocOric9R8wdWrlwC+mdb53zqsZbpd4dmryxyMX+LGzCxJv0u0c4exNnhhjSweY63GkQLHkQgjkIJSw8KWsvWPRduEwBqL0ZpiklkJwOgSiK3WYA1ycvO31oI5EgiTCGvK0rmx5UGxYAxYXfbKYwmZ1YzSiNF4TL8/oLV4khPzJ1k8eZanP/l5DqyPHWiyPGN/Y5Ov/+UX+czHn+H04gzjAkZJhpIu5xan8UhphR4uGTbTSAuugDvXvsHB7j6ffP4qi60qnaqP60iULPv89gcEjceeRlpjLKSFYTCOsNaQjkcobfG8UnTNq9YY9iQKgzYFUuTl+k7k8SWyXDPpsXLyDM88fQVPamr1KmNp8GQ5p5BbjV/xGI4LHm53ORzn9McFDLscOGPSpOBga4MXzy/iX1wm8MBtV+mmEe/cvsGNd95lql7l1Zde4qmLS5xemQHMD/Et7icjjvHrQ4hj/DrGr48ofj1Z5ceCEYrylljeuAvps93PubYVcZh5dDNDXKTo3iGFNYxHKTXlkkY52/1dkqyAwnCwu4MUKXkypO45FMN9ksNt4uE+HgbyDGkGGJ1Q5DG6SNB5gqVAqjJRUMIFazEmw4oU1whyCiwK5TVpNJp4vg9KgO/Rqp+kWquRpzHbD66TDPeQZOUD1wWuKCiSMXPz8yzNVmi169/GcPhvHUJYXAVnFts8ODHLOHWI4yHZTJVH3/hLLi1MkeUF2likVDjKwU7AVUqBMOXPXw76lW7Kjijv1MZoisI+ZmhIKSeklzJjwthS6MuYshx89KFLATDsxLzXlOXiFElkDaM4ZtDtkRWW1uJpTl+8ytLpC7z0sU9g63MMCDGFom9SbJ4x6u5x8cJJWqHDINdsxgkVL2CuHiBzTWBzlNUTs0FBHMcMDvbwQ496s0a7XiF0JVJQlsDfr2k/4Vq/n8U+pvNKieN6BGHI+OCAfDQmLQo8T1JvTpMc7iKKFPIIafTkVIB8TDZRKDfk1Y9/mnqzReAKQlkQ1hwcqShHNwxaF8SZoTvO2d4fEfWHDPf3SKOYNM4xWcLsK5cp0jGZzuimDvfuPOS9r3+NViD4Z//ol2nWFOfPzOGKgkn69rfdfj9ZcYxf/83jGL+O8eujil9PdvkR5UBgucM0Rvjc2oy4/qhLfWqO4cY+uw+3MEBkLOv39+ju7JcdTKnAkUCKyMeowSHJcJNhd5vdUZc8jSnyAseWg15GueW4+0SMSWsN+AjhkeYxjiNwPYUpcjAaYRWTiyqF0QRBgHBcusMhtbaL324TVKssLi8TuA7bu5tYr4kuEoSOsQakUSAkga+oVhX1WsiPuj/+N0epMDpTrzNXUQxnQ8aZRsycIjnY4OHmTZY6bYp4hBDgeR55XiCELku+jiql5QFzpF2BRdmJvL0un6jCInTpYG2smZgBTqifGjJtSbUlyUul06NaZIElM5a8sGTW0o9HjIdDfDfArzbwqm2++MW/4h+fuch0q01RaZAOc1KdY+MRt976a66cX2FhYRZHuYhMU/U9ar5DzTE4CJTVSFFSUFMj2NzZJUky2vOzOEGAchyszXGkwlUCazUflO3/QUKXdBGkgND3cFwXRzmkwxG9YY9ao4qjfKSqImUI0sNklK0Nax7PGxihaM4uMH/6HKMko+q7CGNxpEJKSVJoogwKLUmSnHiUsv1wnf7uHsnhATodYyzMTrc4vdBmquoz1D5vXLvNH//+H6Fkwa/++i9x/mQHJTJalQD1eILhOL4pjvHrQ4hj/DrGr48mfj0528taEJJC+lxf7fLFdzfZHQuG39ggGWuskQyHA/a2NyjGQ2xeHnypDK5rMPmAw+1Vou4uJu2ByZFK4nhVfL+KEqXugTZl2Q6lkErh+lUqlSk8NyROh6R5nywdEMfb2CLCEwrhV9AWAqckShZFQehJMDHKCWm0QtqzFRrVKk898wzrjsPBw4JivIEVApyAMAhRJuJjL72K/FuIKj1JpvU39y4lFdfj6vkTKHeTJHWJoghz9TJ/8vAW/SijFYbYIkO6PtotsCbDUKY4AoG2ltxYRGHxMBN33lK7QhuN1UXJrlBu6W2ji7I9YKHQhkRbogJiDYUpC9GakhWRG0OWFwxHMWka4SuHvABjJI8ePEIpxdLiAkFYIQ9r3Pv6u2xvbbGzvsa927f4xD/9DaYaTbA5SjjUA3ApRdmU4wE5mdaMsoz+KGHt4RpJf4icFySZZmNzm85KEylcHCURfG+Dxr8prLUlY8QIpMlphB5uJcANAtLxgLS/j016hK6HkD7K8XCCGuOBxuocabNyoFIItJA89cJL7AzGtIZjOvUWxWS+YL+X0I0KrHDoDyI2d3rsbmzx8OZNRJbhFjlp3MUK6LRmWZip4skc11bY2enRqlf4uc9+nFdeeIpksMX5s6dwpIPVBfyAZfOj+EmiuH9THOPX9xXH+HWMXz/p+PVkbC8LjjBkBm5tjfnjt9e4vxWz/mgbPR4hhSXPM6LBAB2PsUVEno3IkwEmG5HFPXSRgDW4ysH6VXRRIISD5zXQSDJdTv8LawCnvL1PvrfQkAgBbpOwNc/JmWlGvXUe3PgS6WgPU2S4vluayqVjRNSncD2kDUmlIK346CRGNSpcfOoCvZ1H7G2C4yhcBLX2NAuL01y9tMwLT1/6AZf9hxyT3qu1ltmZBjv7B8RWU6Ugme3wzEuv8qUv/BfOLnboNGuYPEe6HuT6Ma1TIihsyWJQVpBqg7RHG+RI3I0yM7Y5MPG1seXgXJYXJBoSLUiNxEpVgpHVpIUmjUuvmLzICZXAFRLjVejlFsetcub0EhfOn6NWCdgcjrl17SZvv/FF4t4BrcXTFJU2aZwyFRiEA0oqhnHOILb4DighGY/HaAOu4zLq9SHJiLp9bt+4SeOpFTxvpuz/S8qewgRAvvcRsI8zDGEnnArxgTK7AWkLWo0K84vz9Lf3GB3uQTYgjnJEpU7g++TWIaw1SfOILOs/5mZYBFNz8yyeOYt2PJTjMI5jXOWTWsHbq/vsjEEKxbi7z87WLqP+EIoUk6akWYpOM/yKy2svPUfgl9Tow8EA67j8d7/5y1y9uML9O+/wyjMXcSRYWyCE/dDz/Y9iHOPXhxDH+HWMXx9R/HrigWdtHO7tDvjCW6vcXo/ZfnRAd2OD0eE6UmRUqyGyKIiHh4yHB2TZGDkBC98LKKQhzxKkCpBOHWE0QklUWIOsZAdk2RjSaNKYFaA1OhkSFxrhVPB9n0zmHA6qtBae4Wef/xhf/+Lvsnv3Bq7vYZVLlESI6B7JeJ/qzDmmGzN4wrJx6wb3vtbjcGuTg501TNzFZiN8T3DhVJt/8t//Jq+9/BJKHvXKfzQL/32vuS1X3gqL6yqW5lqsJRHGukipcCtNpk9d4d2732BlesSphWmk8UvQNYDJsVaQIVFGYbQEfXSozERkDKwsMcROZDYms/9kuaYwhtRKcls6MVtjyfOCOMuIk4g8jZFGUfVKNkYmHGIsNiupj7/5D3+LmXaHOMvZ66UMDw+I9reQns/TH/sEYXsGLUAJg6sEyhh644LdYWlQWFEZ0xWYboQIcgLpIuvTWNehGUpOzLYJrEFMeviasn9uhUTakuFjvusKP4YPmLRErJWME0GhDXFucaRhttPknhdgshS0xeY5aTKgMXcKZavYPCm/p5QUhUApgxaKlUsvYL2QVqtOrRbgK41wQ7Z7KfcOxvRjSX/vkGh/k6h7iDAGmabkeURR5IRTszx95TQff+Uq0hYkeCR6xM988iorCzN8+c+/wMmFNo1GbZLplzThv1Xq+BMax/j1Iaz5MX4d49dHFL+erPIjLLvjiM2xprlyEb15hyRZBxNjdR9FTn/3kNyCweAGdWphDWMkKmihlIXhBqY4xBKAqlBttRD1Bo5foxbUSYcH9PbXyLRGGItSLtZohMmRtsAWEXHWR0SgsxHShU7nIosrz+MQ0u1t0p7qUKtMYYsU5Xn4jQphEFMPM7JRn9kpj+H9Xeom4qmXnuHMygyf/NRrXLl6kWo1mPTnnQnV8v076IfTCii/p6UEktlOm/29fUZJhpAOygmpTy0xNR+xvnWHvd0Dzp46S92vluArJEWRk1tLnltUPuml8z7lVduJt421WG05Om6lwoRAW4WhFKZK04QkTcjzFF3okiWgLBVHUPXBc3ySXDKMEwwuJ1cWeOalZ3CqIfvDnME44mBnjVxbLj31AhcuXaEe+GA0CIc4txzGlt1+we2HuyjlIHXMxZMzZCYnSxMuXr1KHjS5eGGZi2fnaHqAMORWgSznHoQwExBkohZfvuhvokBOPm+PnutEATcXDre3h6SFS793SG41cVYgXBcjLEI5+J5PkidMz82Tmhr76w/IsgJBObiJsATNNnMrZ0s1V6sxeYEbVOgOY3b3+jTqDfrjHmkUEw0jijihiGOKOEFbS9hocuW5p/gH/+DnqTQbjLKIWGtq1ZBmrcLOxkOUsDz3zNMTWqrmsfmfmLy2n0jK+g8Wx/h1jF/H+HWMX0fxhGwvgfIahHXF1r0ter0+uhiB7VFEO8TDPkHYoj2/Qm12iTCc4uCwD9Ih8CoMdh8yzjawXhN/ahlTWObOXOLE5SukRrGzts7h3hYCCaqKG7goNyDPUnTaw9oMITSiSCiiiMFgj+HhI3rr75KnhisvvsyrK5/l2je+yomFafI0w/d9ms0m1fYU9WqN1e4aZy+c4X//3/1P1IOAZqOG7/sYq8shO0CII+D47vftDyuUUszPzdEbxNRrIbPTbQb9Iel4jiwa0t/b4K3rtzi9OMtsq4bEoTBlGVSK0tZQGwvWTjbW+542ZbFVYk2phYEoD5a2hjgaE0cRusgQtpSMlxY8R+E5ipYvEa6kn/scjDW5VSjP4ZmrT1MJawwzh43DiC/80Z+ztbZNe26FVz79WVaW5mjXJK4r6WaGu9sj1g4TuodD9je2SXUpiz6OcmZaIRWn4PSFs+znBZ3pJh3PEDqQaIe97T5nz6pJtmsp1SnEYz2X7xQCiUZN1ExLs8SoEHzx7bts7md4xJw9NcsoinFcCUKX0wJKYXNFEFSIxgbpBbhBlSJzMBRY6XP2qedodmZpNBpUwgpGKDaHGTu9PpVGm4VQ8uDeOjaLcYRAG0uWJjh+QLXd4MLlC/zaL7zKytIM79y+TzWsIKUkDF0Ggx3i/j6f/tSreL6cTDCIx6/quO7zHeIYvz70OMavY/z6qODXE3p7STwVkEUDdh7dYrR9DxFtoQeb6FEXV0mE1QwPDtBunVRMUVm6iNQZh/feI+1uYo3Bnz7BwtWPMx50WbxwkWeevYI1OX/w8DbRaICTFyi3Wt5QK22ChmTUFSSjHciGoDNcaTFpRNY74KC3Rq0xQ29/kctXr/LUU1f4u59/iUBZ4nFKt9ejP0wYR2MunJzj9U++wMrydHnHtBJLztHRsbakWNpJufbDZ0tMYrIbjDG0W03CwCdMUlYWmlg9i+carElIkiGDw4hHmxvovI2LJfT8UqkTW07yG4sxBmMMRVE8BhEm2ZOxptS/sAZtNFqX5oJYixKlDoVCoFTp1utLiVQusdeiaJyi1pKMN2/jSsnFC5eAgJ1BzPWH+3QTQ+fUWX7ms5/h1Zcu06y4OCLDSsHWsODWfszt6/d49N7bHO5sU2nPUZ+e4WDzESZPeOmFyywtTRPWAqTrIa0gyy0bvZiNtQ0+/5mXJ5nSkYqr/O69czGRPRN2ohdSIJEcHAy4efsRmQi5cm6eE4vz3Lj9CFeKUjzNFFipEMojzzIqtSb7ewIV1hF5g8IqZCXkudc+jVuvo3U5hzAqDAfDglGmmM0FG4822Lz3gGw0Ih33yOIUv96g2WzTmO/wwktXuHp2gVv37vMHf/zXdGYWUUIy3a5iswN+9XMvUq+6JQlpQt09cu3+yOzbj1Ac49eHGMf4dYxfHzH8eqLLT6Etdx/c5+ath8j4kBMNl1t3t4gOD6mEDQqhQSikNZhkzMxsk0qrxaPrbxPvryKLCL/SYGbxNHMnThFlC/itJjvbD/nUy09zbXGae+/55RChnAyrIfC8Gips4+kcqT2KIsYajesoZGoQeU4yGnHnnTcYjRKm29PM/9rP8szFBawyZEWGLgyFlgipqPhq0hxWE0phMSkJH318sFf+YTfNv3kbKFkO1M3PTNPtdqn5DrPtGknSYjiYZ2drg0F3jzSLiNMUbQqS0aDMBIXFGoMU8rHJo5mofB0N12vshOY4mSO0ppSbnzgMKylQQqIosybfUVQDn9irc+LZz3Dy+c/z9lffZGfzLo3Q48ql8+Q6p92q8PKLVzmxsoRrDWcWp5mtSXyTo61lkGV0xxn9ccq7b3+d7XffwDMpqojR0T7jwYBas0kQhviuoFEL2e+NqBgf3/P40tdvsDzTKB2dhQAred++8APL+YHS/5GRZSmoVSAsRFHG9uY+nuOxtLzE0sIUnueSpjmFliingrF9pJDU2w1G4z4vv/ox/GqVu994iyxp4uJx8uJ5ZhZOUAgXl5yKp9DGMkgMO4cj9tb32Li/RrTfJ+vtoosIVWmivACv3mLpxAkurMxR9Rze/NJXWb3zkHu3V1G6oOZL/tFvfI5G6OGrUorsu+3Tb211/DS3wY7x60OIY/w6xq+PKH490eVn/7DP/+t//k+k2nL//ia97T2S4R55FuE4Ejf0QRforMdwN+LRewKsor/1EGki8izFSp9gf5tHN98lbE2zl8ecuHICIwQ6rLP89CskB7vE/T08JZhbPs3Fp59mugZ1EdPv9njn1ioPNtYZHW6ixvuIZIguDFIpov4+e1HEH/6n3+eZC/8MrVNcIfBchXFAKgGmKBcSPemXfvCj/JNvHiT7sOPoZ5jIwFvB3OwM6+tbxGlKvVqhVq1QGHCDBp5XZTwekKYZgeeUJWKTgyjLvZhyGFDIklYp7dFgYpk5PVZBnaxBuUQSIRRKgBQWz5FUwgDXkYwKy/Kzr/EL//hfQNDm5ntfwVrDwokTNDpT+LUaDV/RSgXz1Q6h5+BYQ+AYasqhwCdOC3y3YLEVcvrkMuMH32C8tcnewwHKdcm1YGb2VTzfQeqcxXaLv/zqNYbdCkUac/f+Kp988ReQFFjrMFFbKY0By5TiO6+sFWXJGNDS5dHuLnvdIb4f4gUBuYHeMMKr1MlNH5QDArwgYGZ+nvlTC0zN1JhPlnhw8w64dRzh8PGPf5J2s44QlmYQ4iiPWAswCVvb23TXt0hGKUVRkCUxYKiEVarNFq2ZGZTr4VpDFud89Y2v0t3tYvUYWWhaJ+Z57enT1DwX33EmgmaTUvFHadt+xOIYvz6sOMavY/z66OHXE11+hqMxX3/rGsP+IabQ2CzGFH0sMXmhyHsGR6iyHGnh4G63LGPZDC0NushQQpEeBmQWslGftNHEffYM/Thn7uxFEjnDjnVw3So2G7G7v0/67lv8o3/ws/zMKxeRSnBzO+LWo33uXL/N7a9/lc3710n620gUSTImG+5x81ZAYn8LpRTCOOX4myqH46RQjw9LucbyA6/yqOT27bfuDzeODvLEM8dVzM3P8d61m7ihR7NVY3FhhjQeIfMhd/s7jJOUilK4E7F3YzRCWIyV5TpQKqMaSjEsrChphuJ9EJWCSTZSehAppxTi8pxypqCwksuvvs5n/8n/QLVzgof37rG/9QhHuTRmTnBICIlgyYeWD75ykMIwzgyD3CCFIrOlJHyrFuI7HsPnn2Pj+tcYbtyAeIROBSJsE9Tr5WBcnjPfbOIiePBgjQe3brC8OI8jQUlxlPtOnu7kdx+gw35wSQVMvJ4Eh8OUa/e3eLQbsbWzQyoUs63zDOKcWr1OniVgCjzPQ0jJ2XOnOXv5DIUtKIzm1NmzPLgxpBO2efaZpyl8B4VmabqO1tDPBZ7qszg/xXy7wXCQs7O+RjcfYbXBb7WpTLUImzXCaoDn+zxYXWV7Y5U0GqPzAZ7r87mf+4dU6wGVMMSaiQy8+GCKbT962/cjEMf49WHGMX4d49dHC7+erO2Vxox2V8vBOqMxpsCaAmUF2mRgwAhd9lexoFO0EDhSYPJi4heiiPvbKOXx9Guv8czHP8G5s4vUQ0l1Z0Cj7pO06hxEBxTpiHFvj2S8x1/9dQvPxDRrHqlfx1WaxnSdS5/8DG57np133sCVY1ZXb+KSEMUDRAGOVCDEpJdoJ1Pz4nt0FD9KGdNRvP8zmcefMdTqIVGSEDoenXrAc+dmmQ7hpm/Y2r7HsLuPryRV13ksCmbtpFxqDUWhkUKjpAQpSzn5D/SXhS1XTQqJowSO72CFRFDKnzthldNXnuMX/ne/TdJc4FFvzP29PgeDGJSDVg6PIhgnEVWvxXxgCWRBZD1u7vaQUtCp+oyMJosN000HV2ia9ZBWZ4GHQuAqKKSi2pphbnmFatUnzgqMTpiqV/nyH/4Hht0efc9j2B1gj1yAZakSaicqu+oD9fdyHKJcSyUMthDsDiP+4EvXuH5/n4ODPv2DXQ53DqgoWD67gpQGaQuQLk7QoFav0GpUONzdR1dg9f49zHhMbWqK8+dPUKlXKUxeulC7DtrV9IuclZbiwsISUQ63H/YIggBHOvT396jNLeBVa0xPt3jxqUWaVZ8v/NGbjLtbpRmh4zI3O8tLLz+HF/rYI40TIR7rfDyOj9L2/YjEMX59WHGMX8f49dHDrydke1lskaFNihEGbQx2ok9QliY1GjtptpZmdKVhb+mya4TCOAFec57nPv3z1OfOst8vkPfWmG8EbNy+xe7OAcnhDiLp4joxtSBib/suv/+/fIM//XcOjXpAo92h2Z5j5eIlmvML1MOcLc+hf9hFJ0McRzM/P4OjFIJJX1hMCmvvD5Tz3Vf4owQcH/xpxDf9r1GrMD3T4f76LieWZggrKTPTTQ4HU5xYOcnd0YhhnGG1IXBlmVmUe+1xL1V8y/dRH/isFaU7s1IKJSXSClwp8ByF8n1aC6f4+//8X+HOn2JzL2K/NyDKsrIvaw1xVnAYFQSeh7UFBhgWlnfXD/iDv77NbGeGetUjETmnZ+tUXPDdAIFmFA1BSmwhcZyAWm2KZqtDq15FyYwkS2jWPKKDdYphn8N1iIcvPy5x29K6siwdixJshVQYI4mzgr2DLrsH+8RxTpLAzQdrvPnufbZ3erieiydcoijl2jeuIzxBux0SVD0Ghx6NVo1zF06z3x8wGkc05xwONrdJuofUWg1mF2YphCXRFuV4RLnGdQyuyTm30EFK2BtFLM2E1Jo1ms2Aa9c9mlMtzi62efnqCRbaIa7UvHftOq4bIqzE90M+9/lfolqtUQ0qpZie+Jbd8Tds3W+aGfhpm/85xq8PJY7x6xi/Por49YT2FpPHYQzWZqUAlSl5BtYUWGvKWW3xLV1n6SBViHAqtOdPc/LyixR4PLr3gPa4j5qv012P2N9eg6xPIxjjtj2EcHE7HmnUp7vfgzxjPNAksWF3e0w3sqyc2uONP/odPAvjUR9H5FQDj89/7mdQjprojAn4HrnSj2MIC77rcmJxka/ffITaGzLfqlCrFCzNz3H58hX2t3c52NpE5xEmdAk9Nclej0rQ37LTxPsUQ2FL4ACQCKQogSP0fHIhCaaX+ZV/8X/EX7jI1rhgbe+QQRTTPeyTxykSKAoLRlALHDwXtIDtYcZX7+xw/9EhuxtDMp0yNVfjhZXnWW5XidNSuj6NxwgMhVXMzJ4kx2E0HGLyFL/ukeicaq3KU1cv896bf0E63KHhl+XvMjsUk5JwmT1ZJHFSsLG9z537axwOxoyihDi37O2PqTU63L15n8HBNu1Ok9FYkKeaijfP4W6fE4tzNFpT7O8MaU+3WTl9kps3rjEaJdSmDFXPI8kzyDOWT5xgMI7px4a4GtIbj5lpeXTCEE9KtM1pBw521qNdeLieIkHQrAZcOdXk5JSL0Dn90ZAbt69jlcSRVc5dusRzLz7LwnwHYfWHLmD34xfH+PVRiWP8OsavDxu/nkzkUEq0U8WYArIYaQqMFdiJeZ0QpR6DkqrMlqSLciWOX0cFU9SmFqg0Z3mwus5wdI3W/ApzM5d55tx5fKDmgM5jxoMDHu0csL/9iLzfZXrxDLUZh/2tR5CNcJTDwpkz6NoscaJJ+4cUZozneQShzz/9J/+Iz/7M65OBt5/QdwhRlm5PLi2ytLDAnfuPaAYnqPgBnXabMydP8fVqlX1b6kwkWYYrPRwlkeoD/86kjFy+IViMKiXk1eTwSQRKSjxXoZQiEQ5zF57h43/3N3CWLnJ7b8zq1j5ru/tI5bC6ukY0GuMIRRjWmKp4zFRdTJ6SS5fY+Gzu9NFJSpQPya0mnKuwWA+oqxytIIkTsnGELAzarXHi0nPEmWGq6dGpuLRrAWlRip298olP895bb6DImZ2qcyR1L0Q5GFm+4Un2D/o82thh/3DEg/UD7j7coLCS9uwseHUOuiNGh/tk3Q32hpu41UUyXFydkUQxwliQAr/ic/HcWWqhT783YGtnn+b0Mp3pKdL+Ps12FS9UJMbQTTK66RB0hFENOp6LLVJcJam5LoUV5HnOTNWlenYGmxfMtyt4ApAOq/ce0O33sMal067yG7/5a0xP16lXPRR6wmD53vGdsqOfWN+uvyGO8esjFMf4dYxfHzJ+PaGru4OqTpeZks4pNOCGIF0kOVjNpKOK54S4bohbq9GaXeH0+SvkVtCZX+HWzTskD27RmJpmaX6WSyuzzNRDVuYa7PfH9Lp9XhKWhbai1awRuzP8zn/9Ov/5f/0dGiphf+8hi6eWCKeWaKgC+/IrODJmbnaGX/qFz/PpT38K5ZQb5zEZ4iMSP7Q3HmsR0hIEgssXTvLXb36V28Jw6fwiflhlqtUijWOklHheAFKTaYvnOAhR6m0opcqBs8cKoSCkQCJRSKQQKKVwXBfjOEwvLfPq65/nyqc+z9hr0Ys1w3HMKEo5dfIU169dZ9AbgCk9edwwxMdQcwSOctA4dAd9hoMR586usP1wlSLRtNtNPFeC1FjXodas43oVrFMjbM1x4epVTi0v0K4YTs01sXlEw7ME0jB74SInlk5wsL3+2MXa2qNxQZc012xsb7O332ccF2zt9vizv/hrgvoUK2fOMU7h3p17iFyTpwnYlCQpqM+2mZ6/QGdphmeeOs3SfI3BoINOY04uzeC4ljAIUK5PVuS0pqa4cyNmyptl9dE21UaTne6YpABpNcrCQs2j6Zfy99JRhB5UM0PNc3A9iaM8GhWXKC0QBv7qz76IECGN9hS/+Is/z6nlec6eXEAhJ88NvlP69P2Wg3/qWmDH+PW3jmP8OsavnxT8eqLLj1QOYXOeeqNJdOATjYdUphZxah0QYE2OEAbPcag2mszOLtKZmqLf7XLj7a8yHBzSOXmRqy9/lsRYTp9f4dnnn+Hhdp/7j/ZxKxWiwqUxt8xzSw2mqwZjC3Z1QL3msLS0QHftFtpofM/nl37ukwR5l//TP32dwFflFDulNL1UqtxEk35+uVpPvD4f3RBgrAApGA97zM7M8e6tuzQ7UzQrHtYqkjjGAnNLJ5juTBEPBwwP9tE6wVFl+vRBzQwBCG2Rsiy/SqXAd2ktzPGxz/wcz776KTonTjGyPofdGJkVzFRd1Mkl1nd3SaIBF86f5s3rX0YLw8nz53ADD6tzrACLYhRnCOXgeR4agV+t4IQB4zSjE0gcJIGvaMwtMh5eZmZhgXOnF3nm7AnIRzhSYx1LLVR0WlUQkudeepkv/Kc1KpVw0h0oxyrjOGVte5/+aEymIUoyDrp9Tp85y8LKaZLCcvfafbY2d5ht1MjTlPIfkIT1Ds2l0yxfmKfZ8gkdePbqRVwhabc8pITzl84jghp5XtDv93AdhzhK+aP//AWyNMGv1yi0ZnDY4+L5i+jxC1w9v0TVlbQaHr4rqfqawKuC1EgFUVLQHaYooXiwtsvM3BnOXzjDz3/+ddo1h2YlKKm8QvG9HH+O49vjGL8+QnGMX8f49SHj1xNefkq59qh7QGokzfkLtE6cZ/70eebnOlQqiqlWi2qjxsbDDb7yF3/Cra//Fb2ddUQ+whEp64cbjPpDLr74Mc6d6TA/V+erb+/xO//b7zM1NYsbNpifcrn4W68xlpL+OOONm3f58p/9OZt33qa/eQPhOowGA1qNOvO1kFrNoijZGAZZ9vUtk19RltcmbFD7uKz4444kpXR7YSyj8RgjPaqtBb72jbucPDHPVCixVmGFw+yJUyydWGK23WLY7XHn3bfY29oCU+A6oCbESikEjlQ4ysEoRaXd5uOfeZ1Pf/ZnaC+epnDr9HLDzsEBhbZMt1s4rku/mzLbCGg/c5FkPObd3xf0I43nKQQa5fhIV9CPM2IjaU93GAxGJFnOyZU5Ti1O06yGKJtDrgnCCi996tPcn1ng1IkZlmZa1J0C6fhYkSOUT+C71KuC3ijmyvMv8udf+ENcL8AYgZCCKErY2h4Q55a0gCTN0TpnYW6WztwCOQITZdT8CvloxNDkKCnQRQ5WUWvWWT47z/KJWfJBl1u31piZX6RWq1OvN4iTGNf1iJMcYQyHBzu4AtJhl+72JjoZonVCrnOk8FmXoMOQB+s7nF1Z4sypZZTMyPOCIHRwHI0fKg77OeNUMOju0Y01T1+5zG/+w1+mUXVYnJ8CmwEC84H5hu+5S8S3++P8VFR5vkMc49dHKY7x6xi/vo9d8iPErye6/CjHxUpJHI0I6k1OXLjKpaef44WPP0O7GZDkOXvbQ27dfcBX/uRPWH/7zyDdBV1gKdA2R+cJ+6vfwKtWeObyPKO9Lmt3b7N588vsauisnOPEi+f54p/8MQ9uvceg8LixmbC31WXY3cVSACEbmwfsHA6pCBffZMxPhWALhFAISin0x1mTfN/n5jFofHD9fsQ48qMCKoHFEVCt1RjGMWmUsL32kMGgx+JMs+wrS6hPzdKcXkJ6Ho36HBdnT9JaXWNr9T6Hu48Q2QjXFihpcRHkrs8zr3yMz/3yL3P2/CVQAX2j2N7ps9mNiQpDu1XF0xanKOcnZgLwHZeR4+IpixKSmmOYb1QQWNLCsNNPuLO6zWDYpxF4vPzyU7x2dYWTc1XqTgHWkknFXn+MChxe/PgLTIWCmak6rldgtC6nIKzAk9AIXXpRjg0anH/6BcJKDSElSZKxczBimFsG45QkzrEmx/cUBp9+b4T0XSqVGt1ulyyJSR0HxwvQI4VUHpWGz7nlDjNVl//8ha9xsLfD7NwO7U6TRuBTCV2UFPS6A1pBSDbYI00TKoFPHvcg6WF1RKVSw3p1Gp02ttA82uzSKxQ7mc+DW9cgT2g0Z7n6zDlm5ttsbA4Y90dsr95jdn6JX//1n+P8qWkqniD0HLBmkoV+O9vlO+230tn7p6y99V3iGL9+sDjGr2P8+knErye8/CjcoMrC+Ut87FOf4HOffZWT823GueXW9oh3rm+w9miDakUwMzfLg4nbXKnEqcjzAuE4NJoB8zMVVm/f5O0vfoEbN2+Q7t1D64KtaI3/fOP3+Q9ZgTCaameWztI5mpWArgrwOpeoVDvYoEFvOKDvB1SlQlsHhUFag7IFCAcrPLTV5HmBFBYpBUqoD7QZP4qaGN9/lOMAhqXZGXwBh7ubbD26z/17ETd8hdYFniNZXlpkYX6JcZwx0or7vZT9kU/qncC2azg6xuiYTGeIao3F80/x9M//Ekx1WB8otrtd7q/tMU4FmReSSpgpJMqrstIMmWtqVD4qhw9DH0eBS4Gymjg3JGlRDsFZF50mtBo1Lp2a56mlFmdmQnyR4QiBET5xllDxFVfPLtKu+XgmphGUWbBBIYxA6wRtdMl06I7wvAqvvfYqnU6Lg8GYte0uxqnSHafcuLlJs+IzP9NglGfc2zxgdxgxNTfLaDhm97AHEnKd4VSaJPEMUkla7Tbtqs9wb5e733ibQe+QUXfIqQtnab14lkqomErqzHTaRN1DBt19wkqFKBpgirQUVrOQxRGBWyXqbnKws0t1ao5aLWBnY4t7N+8yOthn+dxV6ksn2Bhss791QN4/oC4zfuPXfoGL55bxHE2zUQVrHvNBfzx37Icbx/j10Ypj/DrGrw8znujy02lX+B9/+9dpdirMzs8xXXHAWO49GvAH/+VN/OY0U02Pi2c6BCen2fzGl9hYGzE7P0eBYDga47oO1VqF7HCVRwe3GPf6kBmk20QFPo2ZWQa9LdqdAGUs21urHOw95NzFp3n2+ct4zVMU1qM1HeCLjFBWULLCYGjBcan4Cs8WJGnCIMoYRDFGF/i+SzUMqVZ8fM9BCTgCj2+9TP44lJTLpLDkg7i+i+c7jKIB7akGU06T7uEBUkh832dlaZFWp4McZowGOXlyyMH+kDwa47s+mVY47gy1pRmWzp3Ba0zzlUcF4sEjdja2iHNJISSt9hRpnoDrkWWS5c4UWhocCZ4XkBuF0SnGOhRG0RsXfOP+Nko5nJhuUa2FPHd5BeVXaARQ98FqTSYcIiMojEAIh4sLbWyegjBI4aFNgSmKsr+vYZwpdgcJj3YOiKKEk7NTrIQXiDK4vbHD+kFKolN29w555+s3mWnWObE4y607t+kOx5w4cxYvytnYOcD1A1zPRQrD0tmL9Jsd9jdWSTJNYQTd7pBkNIJkTJFEVCs+nu+zsb7Og7tbDPZ72CwhGY/wHEWWjSYZ/KRloTPi/h7JeADKI+ptkoz38esLvPz8s2zvrEOlBo7Dzu4+w909vHiHX/r1n+W5y8tUnIJqxUeIiSDYY+O/43jSOMavj04c49cxfn3Y8USXn2rg8trz59noDdnf3qEy1yQ2iv/Hv/333L17n7//G7/G6x97mobr8Dv/8+8SDQeoapOVC1dod5rs7+8RjcdM1XzOrswxPTODkQ3+4q01ehG0p1u8/Oqz9PYekfa2MeMhX/i9f8fuzg4Pb32NmVYHHVUJai2unFzgytIUU7UGvdSwttHnj/70S7z47BUun54mGnYZRSmDYYwSDvVayHTHwwpLXuRUQoWjJqVlxI8FYHxrWFFupKIwKCVpTXW4d2OTK1cuE/hV7u5v4fteOUg5UTjtDfYYdQ8ROsN3QFlLlmvcao2p+RUsHo/uraOqVTrzM8jGLIF2mV/ucPbMCl954z2yTDA/fYJGtUOWJsiiIC8y4jhnlOZo4WC9Kqs7fYadEcsn5tCOQ2ZSzi7PIJWDFBrXEURI+qOYNDdIkzPT9AhsTiYN3cxyGBW40tJQkpoLShSMrGCYG2Y6bVbmJZ7OcJTLYT/HrS8h0pjNB+t87Stvs7+1zeajbW7efogh5+lnn+LU6VO8e+0uhVU0a1X285xGPeTcxYt0p2ZJh11ybXi43Wc0KsiRIDR5HlOrhqytbfNHv/cn7G7uIZw6Dim2iMkiS5ZHWJNNhvkM1hQlc0MXE3+ohP2iYPnyLFefu8JL1WfpDRMKJ+Bga4vxwRanT3g8e2mRmpujhCXwqqUs/vtPnh8UQL5TD/2nJY7x66MVx/h1jF9PGj9M/Hqiy09eWO5sjdk5GHB2rkqnUefLX73LtTf+kk475Iu/+29Z+3KFeljlT//ki+wcbDC9fIoXnr3Ac5dX0MagnTqjGA67PcJqk92h4dD0aM1P8cmPX+L5y0v0D+vkyTn0oE89dPmd//i/8amPf4z/w//wP7Kz32dtc4cXn3uKdsUnLix3D8Zcf7DLjfUhw+wWjU6HdqVNoDJyG1MUFqNcxin4YTllbm1BrerjyLL3/K29xSeNDwN8hC1v544FR0o6Ux32Gm0O9nq02k2ElBzJoCdZSpKkSGFwPEVraorB/iHRcESeaxyToV2YWlikOTNPUGsQpQVplCNdxWgQc/PWKkIKzp6a4cxChYWGQ8MJEUaQRCOUctBY8iIlLzRWeLgyIBrErOsC13MIfY/AVaTRCJMZRr0u25uPSNKI5aVFKlcuENQ9XN8lS2Ie7B7S6w/pVFw6tYBa6DIapVTdkKjX5dqdu0SjIb/wuc9gpM9+N2Jnr8/a6kO2H64SHR6glEsa1jl/5SLLy8vsb+9w+71rpUdQ3MWkBcYvcKShf7BNOj5EZykbW4dE/TFalL1qEAR+yIP7G9y99wibDAkrGQUZwiboPMXmGiXA6AJjCxAGISTCWqQxIA1+tUp9epassHTckPZslf3hkKWpFjvpkOeuvoxyDIW1BI5X0q9t6U9krTnSr/3+9sh3cEX+Tnv1p+FCdIxf3z2O8esYv37a8OuJLj/9ccr67hYvXTjFSt2SFAVvf+0GerDF9kGXoki5n0dYIUiyBKlc5ueWqdbazM7NMz09Qzf2+L/+3/7vvP21dxDW4rRm0U6NUwstFlqSr/7VF+j2Y6anmpzoTNFePMmVT/89nv87nyV1q1y6NMXTT50DIcmSglEqeff+Lnfu96j4Prevv8PDSydYfukKYQOmGxlpAZkBx1FoIdAoskIzHGkCFzwPlFI81lj4trUVH7n2ugCsAIymXg3xXAfXd1g5fZLNjS2SNAKpQSqskIzHMViFMmCjhGzQZ9zbB22pVFqEtRaGClu7PS5cOovj+ezffsTGvTW0KDh59QrpKKHuGD77/ApnZn18kWIKTZrlyCzDNwITDdFRREV53H/vPd594+uMB11mV85w6aVPsHLmDMsLU2Sx4a2vvM1f/sHv0t+4BjqmNrPML/7qb/IPf/XnmWq4dFzD2ekat6MRq4+22Q3r+I7P1v07PLpxnXEcM7eywq//ymeZW1ogNpLx7iH3H66ztbFFNhxDWhA2AqTn0RvF3H+4xuqNa3Qf3sUWKX7VR1qPJE55eO82N9/7Cnlvm2TQY39jmzwrabVGSIQohe+iqMD3K2TJISYfo4scJSQ6zyYO05ZCZ4AGUR5WY6FQEkeWff/+bpfb797gS1v3yUb77O3v0zlxiaS3x8UzyxS6wKDo+FXEhPdj7eMn/y074Qn2zU/x8PMxfnGMX8f4dYxfk3iiy0+WF4y6EX4RUxQOb1/b4M/++PeIh2tgxlhrwCiMzUBKao0ZeocjvvqNB9zb7PLKiy+y10u5s7pD1O8idEqoJUHDsDRV5d1rt/nK195jbukMI0dSm2kyf3qKj3VOsHzmDMIBqSSBq9C4xJmhl8SkIiAtLE+dv8iv/8rrjHdXGXb3aS7M4QqPsCIwSLrDiEFUMNOq4bkuOi8YxRleZnBdSyV0EZRlPsuRv4qYnFIoJ+LEpFxrPgI4YimEwav41KsO9YqDzmq02m26uxsIa+m0O9T8gKiwjMeG27cfsrt6nySPcbRBuTWC+jSOW8WkGXMn5gk8ODjYxRWaRjOgMtXg/NlFWhWf+arkdMejKVIcCbkjkEqilSLOYsa9Pnmeo6TLwU6XwK1ixgc8eG+Hra1d5pYuUPFc4nGP4cEW6cFDZNoFMnq7D/jdf/f/RknBr//y36FTdah3aizVTjM8f4rdw5T37q1z4/42jlPhc7/4SS4+dY5Ws0ov0QwywzDV4Dg4lSqV6XmcDszNz9KYaVKrN9h5dJd7194kHyW02nNUam0Kt0oyOGBva4tseIDMh+RRn/qCy97OFo50cMM2ruPTatQohIMb1ihGAY6URFkEgDAGgUYbjTV6sj/k4zckayVGWIp0zHDrPl/bu0f/cB2bJ7RmTzPdauAnVYxXZ6+fsDLdxJ28qX07YPxwLy4/De2wY/w6xq9j/DrGr6N4ostPverTrjukJmVrDL//p3/Fg1tfR+gxoLEYNApklWZrmiwv2HxwjcwIZpYv8tU3b+BWqqRa4NWmKLIxKgjJtCE1klvX19g/zFk512L9MGdr522ev3SSk2fPY7WlEYQ4wqJUWZZTEnzPI8k03W6PO8WYZ66e4WOvvUI62Gc4iqj6PtIFXxhUq06cFfieg6ssUrpkQlIYTZrkRGlMrVaKN2ENciItXs7qW8oG+8Tx+SMAHVC6TLuuZGaqxsa2oih8dNFm+8EtHOmwsHiCalhBGMv6wQFZbnErLbLERTkKv9ohaE/jhiHTc20qrQppkVMUBVrnzCxM4TUbKDIansKlIBo7uI5FSouVAl1oNBqrLNF4QF5kGL/KqYvPkGQOO/tbtKfqNDqLFOOY7Z1HxN01ssEmthgibIa1Gk9lnJxtsjjXxlEW1zFUpKBacUhxqAUexj2LG1TxyHnpqZMo5bBzMGQYQJTHCKGYn5miUw0YL8/jKpepTotWu8LB9g5f+r2vEQ/3qDbmmVo5Q3umSUKVrfsZWZagBEipiaN92p0GD9cFSA/jVBFK0a77ONUqWkocrwY2B50g0FhTYCgwttwj4kihF4uwujRdNDE66zE+LHvrwqR4QYtXP/lpVh+tMzOzyPW1QxZbLs+eWZ7suQ8KoU6Kxj8E7PhelNKfxDjGr2P8OsavY/w6iie6/FRcyfJ0jX4Mj7b3ee/6HazVYMpvLIUidxyWT72C5/o8vP8GwkR0N+4QeDVSLdnb2WJqZg53ZoVo2EP6HsJVCNfjcJiC32a3F/PUlYtcWG5w9ew8g6hg9f4D5twFmssdjMhRCpQsDet0XpBlmihzWds95JnTU0xPTzMaDomTmGa1iS8M0oIXergKXAmFKct51krSVDKMEraGI+oVxXyrRqgEoLFCT/IkWRbwPkDZ+1DDgkIhJZw8McfNu/eoVnzGowRRcnQ5fe4SRiqkgM7UFHMLi4wTj0qYY43BqdUIGnUqtZBqq4ryfDQu41HKwe4+swtz1JtNpB9gvQAZCiJtCRQ4psBqQ6413TgiSwu6vT7GaIKwSnt6hrt3VpHCQWhBf+cR49EBebIHWQ/yMU7gMze3wsdee4W/8/rrXL70DNVGAyENggIlBMZqrMloBC6dekh/uhygOxgWXH/3Ol9/+z2WTp3ghddewpEudd9nZm4Kh/kS4HSBRPDX77zN4eZ9KBLa7SlaMzOcOjPHxnZO16tgkgQlHawQjId7VBs+U7PT6Dgm7h4gPBeBpd2o0pnucBBFkI8RVoNJMDZ/nGQLKSbn/oiRY5AY0AKrh2VmLkBKn1prju2NVTbv3WZh+RfZ2jvk08+8gO9KrDjK0D8ab1Y/znGMX8f4dYxfx/h1FE90+dFWUHg11ndG/MF//Svu3rqOyYcoVaCsohAKrzrDuasf542/+H2UMAhHkuU9djZuMb1whmywy1jmLFx8Ea89Qx4ntOoOZ07OMzf7OjsHY5CSSydavPjUMtOhwZ0OOd+5zG4v5lHfsNz2qCpKI0IKZudmmZ49xGQpg9TSi3JaTUWn3WQwGJFGMdVGBWkp1RaEQEqFtrx/s1UO1qsxyBzu3l2nGXS5vDzLzFSIFGkpyW29yZJZQH/b+vy3z57F46n8hfkZfN/FSQ3WKrQ2KMdnamaJODNUalXazQorS7NoGTLXmUELyyhPOLG4hHIU9dlZcjxu3Vxl7f4W2WiIEYrlS+cRyqMbG9rNJtYFtyLwScmSMYO0YH1vTHeYcGt1E6EcjMnZXH2P+GADJ9+mvzNC2xxJhrI5nakpnn/x07z8qdd56spzrCzMUnFBSRdjC5ICksIpvXmEJtcZhclJ0pSqH3Dn7iq/+6Uvs7X6gIPtTUbDF5g7cwFPSbq7h4RKsjjXAFKUhbX727z3znvoIkdaQZ6mOMIw7o9YvX0PPR5RxH2KLEJqg8wL5qZqiKtPsdmeZ/XWHYrokO4wZWW+zvT0LIP9PkWksVi0zrFSHAnxTjRMJnRee6TUCwKJoDTRtNLH8eq4jseNd9+kM7NAteLx/KVlTi92ECIrS7lCfbcNcBxPEMf4dYxfx/h1jF9H8USXn/3DHv/Pf/vv6e0NWLu3DuME1wqscDHWIIXL/MIFsiwjSfYQaYIQEsfRiOKQ/p5FpQmDrX2cwGXhymfoiQCrwPccPvepFwlsmZkU0mUQ5xwMMuZbkoZv2Q9CvnZnh+rVBYK6ixWaQhsqlYDZhTl217fwwiq5UGTa4DuSqVaTg8NDojgv9QawCGsxBrS2WAOOkriOpIgLnFqDsWzz1lvv8tY3Vrlydo6nLy2yOF0rb8hCYCbF5KMQQmCMQUr5Xdfuhx1Hs2N2UsZuNhp0Wm0G4wF5ponjBOlW6Y41c25IpVKlWvWoPFfj6SsFizOzJKagNx7TaM6w043Z3BuwtT9m7c5DinGCQLKweIK5doNOqwJFBvGISr01EcHSCOmS5Rmb2z1uPNji9p2HCOmAjtm88wbx6ACRxXieojXV4tlnX+XTn3mdZ595mWZ7hnFhcZSDQIOUFFJxmEqu3dng5u11ovGY2Zk2p84s4YQeW4cD7l27y5/8l99j++F1RDEq5xjSi4xGMdIKbt55hBeEhPUKOhtQ91xWN/donThLfabNxr0bGCtwTMGtd2+w8/AOjklLl+9iiJAaYTSNwOK3F1C1DkbCYPsBw7xga/eQeDzG8wMcW2Fky3chIR2sKSgHT/mm2m7ZdpAgSutMpMTiENaaRKMupsiYO3WKSxeXeOH8Aq40lPyMj17G9OMax/h1jF/H+HWMX0fxRJef3sEub/yn/y/GKKTXpOJ5pFlIVhQ4QqOER+hXufbOX0LeK6WssZgsx2QF6XiEIxWu63Hw8D0EoN05oqDNn37pXaqVgBfPLzBVc9iNNO/d3y9vm45P2ysQbkgvykl0WYYTAoIg4PBwk9E4ZjwY0Ov3GScddOhQGIOvBPVaje3DHivBDIGjKIoCO8lw0sJQWEnoOzRrit39hMT6jGmx9mid1Y1b3H24y2devsCls7MocpSSE7HKo/7lt0tw/7fKoCadWXzX5eLZc9y4+afcv3MdqQROUMetTNGcmqUWKqS11GsBrigInByjFHP1FmNcvn5jjTfeeI/DvS79wyEOUJ1q4/oudQ8uzQS0qg3AIo3FFwarSwZBu1nhlecuM794gs33vkRXaBQFU6HL8sVnePbqVV588WVOnTlHvdUAoTBW4DoOIi97yQrNKDPsxTn/6U/e5ot//jV6B4ck8QjH9XnupefRNqG7t869t75M1ttGZD3QOUZU2d/ZZOvubXYOurRn53GrU+z3YxY7DWw64sVXXmLu4tMMRxF33nqTr/35f2Rr9RajSJOPD9F2jLQW3/fIMk2cjCiyEd6MTzHMWTw5y6tPL+BQ8Pbb19l88ABhLegxYMCCMOXTKPeW/baZPivsJKWSCOniulV0nlHkMZVKk+eee46Xnj/PfKsOwmClQnwX77/vRAH928QP+9/7KMYxfh3j1zF+HePXUTyZsalQuH6DSrOJ25hmeNBHkeOkHiKLMXgM+gcMDx/gFBlWWIzIy0NmLEoUaJtR5KVPSXf9Nk49Yup0i9WNHv/r773Fu6dnuXBmlv1hxJ/9xduIXFP7R5/jqdNNotwgXQelBNIWZe/agi0MeZozHvTY3txEvXah9MMRpcNvEASkWvJgfZeLJ+cRUpIVhsIKokyg0QhVELguoSvZPzhk93BMb5jR1Qm57qG5i5WCy2dmkbqkAL4/BS+I05zBcEyn3cJ1PqhkUA4XWmPR5Y+LlKDk41mwbxo/tJN9dzS9LhCP//Co/Fh+Skz+fYmcPOjTK0tcf/drRMNdwOD6FYTj4fkBnmvxlCx7uVohEDjSpcgEGwcDrt3fYW8/YrS7i7SC9lST6eV5wlrIbKdGM5T4QqONBaMREqBAYQidnMW2Q9VvUVMZLppnnnmO/8v/9H+mWq/jK4lyHLSVaAtpUeA6isIUOI7AwSKFxzCCL93a4q/++jrbq+vIrA8mIRcB1974CtpEjPbuUgzXKfIBViqU8vD9CuPeDl//s98j7CwyPTPP/QePmKo7NFSd07MVCH2284I8Dqm25sHmrN17l0rrNNVKk2gcU+iUVmuRtHvAOIl59GiLMDjJwWiM7e5ydfE0WZJxuH9IMuiDTlEyQaInz+aoD3HUOD86hOXnxETrQgoXoSpUghZpFuG6LtOtGT7+7GVOzTfxpcCiMUYhUBz5Oh3H3y6O8esYv47x6xi/juKJLj9hrckzn/kc7Zk21UaTLDWsPdpgd3MNGw9YOXWBd778BdxiCJRDdsoqsBYr7VETEYTC9ZsIv0407uHEO9RaDXYe3GH9nS/zxzbBrdaIk5jRIOLPTjRpt/8OhW85NVOl7SuMESQadoY540yzfGqWzTvvkoxzxuMc2wzK3ri1WAFuvc0X/uxNOq2QRq1BrC2bhwPWuhalLKqXMVuvUg1dgsAjjROEtqSjhLVxghOGLGxG1CpDVmZDlCNQomRV9JOC/+V3/oz7a32euXKBX/vcs1T9skyY6Yybtx6yvTcm1h7jJGd5ocarT69QUWXJXVuNBIywWDHZZNYghEOUaEbjIdVqhdD3sLZACYtBIoQCUzy+9b755tusr+0hHBdLRrXqc+7kHAtTJbtAa0te2FI8DE2UG7aHgnevrbP7YAPyjOn5RarNNifOLDB7chnp+mwcxnhKMFcPqUpNqMBRoC2PGSVZphkNBkTjERiJkR5jt8Uo0QSOhx0W9LOUzVFC1ZestCqEjqIoEqqBJJAKF5fD7pA4zqiEAblNULqkSorskKi7Rtp7hGMLFAJrXYLKDNLziaIt4v46mBdYvdHErTXxzy9RO9vGBE0eHKQcjGE4HKOzGGXAcy2f/sVfpJcYbnz1S+w9+EY5oCcchNY8XNshDPcYWE1gA9669hCbJOysreMqQ5blKErZ9qNk6QgorNGPqcYltVgiRendJIRDpTZVamHYAikCzp0/xdkT09Q8By0NTHrr78dHt3z84xLH+HWMX8f4dYxfR/FEl5+Z6Qb/+Dc+A65XMiQMqM88Dbmm3aixtjPgrb/8QgkWtsBagRAW5ORWiSpVHnGQXoX67EmS9dts3P5rDrauk6YZWdwHnSNVBcdz///s/WmMZWl634n93vfs59x9iX3JPSsrs/atu7p6J9UkmxRJUZRIi2ONR7I0tmFYnjFgGPAXf7YBYyzAMKyBRQ1HoiyKYrM3Uup97661q7Kyct9ij7gRd7/3rO/7+sPNqpY0pMSiu8muYvyByCgEKm8g7z3nd573Wf4Pxqrwxmuv8ewzl1heL7HWqiGloBtrNjoxr93cozdJaDV8wnoN4QXkBiZJQtlxkUKQm9ko6o3tQ7703Rd54cMfYag9rmyP+OJXX6ZRazBMMpYW6nzyhUc5s9ziSsPn1mGKi0tWaDqDgs2jjLNrLp1exu3b13n5+y+ytDDH6Ycv8L0XX2VnYNFNBfVGiY89fQILw3devs63XrxFe+Uc7fl5JkWP21tDzp8yWJGF0ppCaGwEli0RRmA9gMFWZ8hv/4vPs7PbYWVlng89+wQXTq/QqDpYtplZj0uL8TTnzsYO//R3v0BYWWQyPkQiWV9d4dT6CoFtI7VBFQVSCIqiABSxsri13eX1G/dRQrC4tkRUr1EoG2EF3HrrDlpI3EunWKw4ED3YPSQKlDEUwmasCrYOYzb3eyTTCYMUChnQ6ee8uTnkMM25d2OD/l6HwrZxmvPMNct86PwyVTsnjHyMLdFWju8anj23xO0bJ7ljW+SH4OicUBZ0d2+QDLcRaooREvPAsAsEyWREkU0QOBTplGS4jzFTAm+JuDDc3h1wMIZpqkinU1SRo5HMLyzywgcfZ7OfY/IUNTlkOjpEWoCC3l6HibtLaktsx+OHN17F0xm9nQ0sk2J0irBBK4GFjZCC2S5MgREW5h20GhCaAo1r2eB4VNvz9A47eFqALnjk8UeJ05jAbfCjs7ThPzxX/+n6cZsXvh/H3o/5dcyvY34d8+ttvavgJ81yvv6d17Bdn8ceOs2FtSYLtQDPssELsQOPsxee4M0fbCB0ijGzTnKBQBgLg4u2Q2TQRJaWiOZOITt7JL0N9GR/tnVZGpTWSJWgC4HlQZZlswmIOCUoV9joaw4PY67d22OnO8b3Inbvb3Hy9EmyPMaoGCkDtC7QxkJIB1Vk7O4e8TsvvkI0d5L7Y4/xMGc8Srnx2vex3Qp3awGWFnzyAw/zwjMP0znokwxSbGXQ0uVonHMwyGhHZdbWLyJklc9+5vf4f/6Tf4qyQqZUyVPFH0xi/tk/+e/J8oyzjzzHqYeepN5sURiDkiFFlnJ744hBJMkLRXfYZ3u/y1FvhMkNgSNZWJzj7u6Y69uKwTjk+ov3ePmNezz76CmevLjG0kKD5dVVuv0jvvCFr/LDqxtMqeCUHLxsgopHnD65RuDaGG3IFQjbJ5nGpFlOtRyiU4eJklhhidNL8zz52EOUag2+8e0fMhjE3L+zidIZ1VBy8UQbIRwMNnFuGCUZUwX3tvpcvXdIf5Jgsv5sN44RTFJ46bXbZH7I3bsdpr0e5WqNbLSHSTSfubNJs11jeWUJOx3y6Jkm862QM/Nlfu5nnuHlyyVMeoLlZp1bb7zMH731NaROwfIwljerJzshyijQE4RQeKUm0pKMe0dIS5NmBRudjFGWMYkV3cNDpE7wjKHaXqQUZlQjl1j4BKUyThQS74/x3IhCC+Jeh1RukGrBcNLncPtNyo6B6RAjQeqMPJ2VEGaVkWx28sV6pzFQChB6NtEiHqT7tbDxqw3igwOsoqDeqNIbj3FcdzZJ8Y5J3awB9ae5afC9pGN+HfPrmF/H/Hpb7yr4GY1jbm30KZg12tXLHtXQQtqKOJsSJ4oTD13g8uvfpMgH2BIMBbN3OgCngVdfpjx/Eqc0hwhK1Jo1Ol0JmULlBiMlSBsjmNXEVYbj+ewPcw7fugc3PGzLZXA05Mpbb4IfUG0tMOwcsT5/kqXFFq1AUvZsXEuCMWgDooB8WrC9NeJ7P7jKtLRGZ7tD3B+gkzGO7ZCOCr73vctUA8PTTz/CmTNr3L7foRqWiSouS2srZEaSKUPJ91k9eZr/xX/9j6i2F/nnv/M7GDtDxwUv3r3C0voK6+ef4uT5i5w5sYQtJYM4oyiFkAtst4y0ILAFTStEOS1GxQE3b21z785t/GiLWmsN48/TqjnU8gU6O/f41ktXSbOMdDJgkmbsd464ceUGDz/2NK25BU6sr/DF37uJEIbVpTlsS5MVCiMdeqOY4XDI/FwNadu4yiKwDR95+gLnT82zvlBllCh6F0+zd5QgLMiLKX4p4n5nytEgZ6ldxVDQH0857A64c+Mu+3sdlBB4YnYqERhyJdjcOSSoNymVq5RLJXzPpt8bsnfnHrtb9wnbdZ4VgucvnqIUeqgswXckj66VaIVnsYTN5uYO/+rVV8Ct4JcaOKU5Ko15nKDEaDgkGRwyPtrAFk1qC2doNpbQWvPBjz1POLfAwVQyTgq6+106u7uEnqFRsik3Fmm3AzIZMZiM6Bz0SKdTTDbFDSoo5TDs7iGmHrkWkA8hOWQ8HCGMxnFClM7QFFiWhVKgJYCDJe13+iHAQts2xmgsk6Kky9mHn+SjP/sL9Po9Rp2M+twcrVaN5eUFpMh5p9NQiB+3EepfaR3z65hfx/w65tfbelfBT6EKhoMjbD+k0x1yc/OAZuhiVXwKUdAsBTz68Am+3ZrjaLoPRY4lbBQS7Ai7uszZpz/OyoVHuXVvm4O7NyFJZ6OWQswmIB74CmBJjFZYRlFkisOjmE5vxNbmNq4Fca/LeNBh+eRJxrli1O3jmSUeWm4wHxg8rZEKsAVJoWcurFlGWFlkY6tDZX2ebueIbDghiEr4jRBL2fQ6I37wgzf50LOP8Pjj5xgjWWq2aNU8Sq6F4znE2lAyBZZtExuLD33q19geal59+Q3IMjob1xkNfZ5+6nFWl1tUA4ukcHF9C1fHjKYpQlRxXQeJwJIOC5aDXlsk0x5TLYmzGOV6CFdxeLjH8so8zYuXuPzSd9nY7aOymEmSMRpDkkn63SN+4Vc+gsGQFjmO6zG/vAJSYlmSONPESUKjXqNR9pFG4diS5y+uUi1HtMoWrqXp+y6XLi6RXz8kK1qsLs8TpzmvX91if2ufKHKwHEG1VqGIE+LeiO5+h2E8pRwJlJpd7X65gpI2xhLU5uvU6xWkSmk2QsghnvY5dXqdC2eWWaj7lG0I/YBhnJGlOc3AJlOSw8M+H/vFX2ev06dcrtFamCesVBlPcopUMR0ecfX1V5A4rK6t8KFnHyYMBamA69tdtAkZHHYYdjs4lsGREMcpaS4haPLS9V1ef+MaW/e3KZIUiUIKgbR94skYuzjA93ymSR+VJdhotI7ReuZ4UeQ5UVQHu0KKptpeIE1zVK4QQqKBcrWO63tkeYw2ksaJixx2+widY9sOi4sLPPPkJQJHMnvSzbZd/2jU9N2dnP5TKd/34xTXn1XH/Drm1zG/jvn1tt5V8GPZNp5tQa6ZTgru7Rxxbr7KQtWj5PsgBB957gxF8g/43d/+f7F3/y2yLEULC2mXccrzlOZXOXXxYRZPneT7f5Sze3gfKUO0yBBCI4SYNUppA5aPFi7TaUISp+RpgZ7E9Ab75OMuJhuyfeUQP6qCMQwO2zicI3QsjFbkucKybOIc9gZTJklGuTlHqVahSPqoNMF2AgoDvaMeiIB6e45JWnD79gaLJ1c5v9ZgsV2nFQgsBbZlk6mcqQItFJmBw0nOM5/4eaK5U7zyja9hbQim/Q7tSjDbyGtcrtzfY2GpRbvdRmpDmhfYToAjJapQIKFSBt+XhKGH68ITT10kKtW4e3eb115/Db9Zw3UdEAbbEnz8ox/h9r0tDrZ3WF1f4olHz/Cdb38XCXiVJtqJ0MJGmBxdZCzUylQjH1tqEBaWtFn2LMoeeJaiMBJhNFLlrDZtnj37KEla8LXvvsnuxhb5JKW7PcB1bdJ2A5WN2bt/m3Q6Jmy00HrWD4GQCAuarRInT7SoN8rMNWuUbfAFZAWUfEWr1WI+kOhshAkDjJKowmCERZoVKG144snHiIXPrfuHeEGZes3BdS36g4QsN5QqZzl56SGm44yKrzlzvs2o3+fam/fZ2RvR6ewwOjhAZTFRJQKjGfaHjMYpKS73dvsUysIWDpm0UUBW5Lh+lTxJSMcHiNwhiRPcICRPNMgELWYL/oRRpFnM2slHePyFjxM127x+5Sobm3uUohIn1pZ48rELlCOfAklWwA++9x2+8Af/HIb7lMt1Hjp/jrMnFpEUD5gh+Pc6EI/1Y9Ixv475dcyvY369rXcV/GilWJlvMZoUDApFZxqzMxmxWpSIUo3ScH+nz/5Rn2leoCybsNFGWyFBdRm/sY50SwzGU2oln4XVVTYu2xjLB+tBvVA8WIRmwA7nccN5cEKOjg5xvQDXguFkiJp2kfmYfJQz3r+NheH1H9i88IHHOdFoI4UhznKwBdpIhpOMUrVF5FhcOHeCN69cR6cxlrTJTU4+iSnP13jqI49jI3jx8i3+zvk1nlirUwodSpbBMhbTRFEYQW+qsRxDmuVM0ozNvSNsx6VIE7QyFGnG1u4BvbsduoOMuzsHfOiFp3jo9EmqtRqq6GGERFizMdpJblBGUi0H2Dpleb7GUxdPcjhI2HBcMHCwv8f62gIVp8C3yzz52MOcOXOak2tLzLUrOK7LzuYWKIUX1BB2gCUdTJbgSqiUZrCaKotxlhKEksACBOTKIkNSaE3Z0tRaPu2SRBkP65mHObm0yOU3r3L/bsHi4jKHRwf0h0fgCkRuU6lViXyLDa2xhGahVeavfeRxlpshgS3wpKJsCVxpSIwk/PAlbCzqrsC2c3wXTJbhSckgTRlMYpqNNp7tEUqPUaNEpgSBlISOhfAkR8kIzwko1yN64ymFdNja73H3xgZvvrnBTueIdDpktLeDHwTY/jx+tY7l+rhhiBuUCKp1RAFmPEBNq5gDG42gVKpSKNBxn3jcw1gRzfkV9rfuUBQOpaCGSacUeUZaKLZ3b/KIfIFKq8KFJx4l9wNUXlBfbFJvh1RDh1S7bG512L57HTXcJzAZy0sLPPf0E5QDe7ZMUIgHJ6efxvmI97aO+XXMr2N+HfPrbb27zI8QxPGEcqPBQrPGfCui7NuMxwkHWcy1rS6vvHyXl773PbrbNxH5FLd9nvMf+ATPfegFhr0xP7xxn0Gvz+DQkKYpUbmBGM8zVQXoKY4XooSLsFyWzn0AGTTxopBe95CoVEdpTZ5PKOJDrDzHUKDyIcJIOrev0ukMmKy1KcucONcM+gnV0gw6dlDGdWzOLDbp3hfseAJJgOs38QKPhx8/x1PnF1ioR3zz1YzpOONsq0SWpzPTLZFjCc0wFUwyQ5ooRpnm5tYBW1t9uneusXf/NkHzJJZf4bNf+Hfs725jWS7VhVO88XqZlaVl1ucj3DxEGQukhbAElciiWbNZqIe0QkGS5Yx6A/Z7Cf04YzyMOX2iyamFCDXqUqrU8XyfEnBqfYVyNeDO/SPeunYPYzRLrRYnF+fwhCJVBcLxOMosbt3apZsUCEcyP1dlqeLh1G0CR2MJKNmSoDQDuSMKhIRLizZL9SZLzcfZfvRh7m4dsnW0x9qZ0zQbdbq7O3iBTSg0V9AorTi31ubxlRDPAkeDa4NjCSQaXyvcqjVLYaoCjKHIBYNJwY1bm1y/d4cXPvpxcuGgjA1aEIQ+UmlsV+B7Am1sxrlHURiKXDOcTklTh/2DhFtX77K/u0c6moJWWCbH5AZVZJSaLZR0meZjHM8jCDxEs0mRTxl16khshGVTaq2QWSHJ3gidJ1jhPI3FsxzsbWMZH+mEpNPebLTUeBSTEVdffxPtlrDLFVq1ClJrXN/jaJqTIdjvjrn+1j0Od/dxjMEJSzz62EUee/jkbKrIiFmmWPx0n5jeqzrm1zG/jvl1zK+39a6Cn0atxEeev8SVWxucrEkePVGjWfLJCsk3fnCFb3//MpPuEcVwE6fIEMZCZZrHz67zM08uUSn7XL+/xNXtCTc2JwwGI8LKHCKLKbQiHx+ilY0TVQnqy4igQaU5R56nqCRm2D1CUiBFQZwMcXQBokCpKRiL8WTIG5ff4uT6HLXlEpqcw8MDqlGZs6stzp2cZzKNqdQilueqXNuMGU41UmskBQv1iOWGz1Ld5mNPnMIqMjwnwBIW5u2ttpbAkZJcKba7U6ZaMowLxuMRe5t3KVcqtM4+w3x7kde+/rtM9m9h+yGT8QAlXHZ2H+bk0lkcEQAWRaGQ0iJwHYTRGGOolkOctKBQM/v73a1NiiShUa0y124wdh3sUoXYCCwp8AMXLRxeee1lOp09JIYz6wtUAkGSJuTSp5fYvHZ9g69/7UUO9jbxXYdKtcapMyf5uU88x4W1CiWnwEOg5czPwUKh9cxK30NRcgpsFRMPDnnsoROcO7OM52qma2UiW6GnKd8QgtRoLqy1WAoVGIFSNsKSCGMQBiQKD4XGkEmL/kRz8+4WV2/d4/Urb/Arv/Kr2G6FTEvSB4ZsSI2lC1xp8CyBCBy8JOLlN2+TC494qsjyCf3DfToHPYaDKSbXWJaFxkGpmcHaZBojLAfLcbCFwGhw/QDHDbCc2ZcXlKg158kUpB3nwZCzJJkmKKXwpIO0JLExSKtK4NaxLEFnd4fK3iHOJGfj7iY6yxhOY4xjU6mU2O8M6B0eQDbBoPCjkA9+4Cnq1QBjij+h1v3jPzv9uEdK30s65hfH/Drm1zG/HuhdBT+uDc88NM9D6w3SeIJJRmgPbOkx3wjp7d7lcOsOJj3E0jFYJZxSyNJclXkvJZIFjdNVzqwu8G+dbbbeegspbEqtdaywxPRol2lvH5ULovoKUbVFkiZInUGaEMcxtlF4tgNGPrCI10hpIYykKDJ29vYZJoZuCq7tUquUUSpjvhzxoadOs9MbUolclpplWrUBUyRFmpEVcNA5JE8y7EJyuuGTZTPbcmkJtJqN/BkhkWLmhXB7Y49RLrHdCN9zcB2LnW4HcbDDifUzmGw8i9qNQkqBlA43bt/noVNL1D2oBC62EMgHvWECsKTEtiRhEFBuNykCRavVZOvmPbZ2jji5soRfX6WXF6R4NHyNkIruGPY7XfJsii3g4sWHMGgKA5mW7PVjbu70OJgotNIMjgZkmYNTHvPm5hFeyeFEwyeSGsxs346YZbRBCEq2zZm5CqFjs9w4S7VSouRb5PGIJMjxSBgNwBIaTxrKroXQM0fVQgsEBbaYWcQqY9BGkGSG169d56UfXscNauwdDfjwJz4N5SXuDRWpytAIPNfBkxLLQFYYCjMbt+yPJ+zs9bCciP7hAa6KieMpWW5wS1XqjTau53C04zHtdUgnMZu37xCVa7iOjefa1GtVlLDRccxeECFslzAqU6rV6Q0nCNuffeYYsukEaRRaGYQMKM+fQwoPioJsuo+Oh7iOxcJcm3g4pXPQIQoCGtUKRgjyXDPpd1FZjLRdTp89x1OPP4LQOfx7TrjH+snomF/H/Drm1zG/3ta7Cn6MgdGgi+eHBJWQ6WTKwWCE4ymW5pucOX2CpD8glYY8OcSNasytn8aNQvLcUFgGIRVWkWKZGIqCPM7wPJtyfRk7amOVtpkOO8igTKYNRZYy7R6QJVM812HQ6+LojMAvUSQFGI3AwRiByVP6nQOSVNNPBSaesFiPyIqMwHE4t1ZjYaFK0y3I6lVK4S5OKtCUMKlmv19wY6vHenudsszxPAspDNroGaiYTXIoDb1xysHhiM39LguL8yytnGR60OFw9x7DrctckwXxtIuUFtKvE9VXcaMmozgnx2Ga5xwNYxaaEZYArXKkNWsU00bgujYqz5iOxoSlEtoO2e7EfO+1O+AEDJWiHFaoLjoIYRhPUpI8RakcT0rq7UUmaYElBJXA4sxak3FuqFbKpOoZ+od9XEtw7vQi50+0GfWP6MkS5WY0WzX4drO+MEgxW9boWoLT8z4n5kOyrIAio7A1iW0otGFz1CfNY2wUaSHZGQk6o5yDwy5nVsos1z3QmrQwDIdTOp0uzXqdX/3rn2L3aMTBULF1EHPzlVvgOeRK02i0cTybSmjR8B0mhSHRik63x/dfuca0P8GoAeN+F88GN/BpLi5jeSH1uTZe6BHWXLauKLLpmGw6InRc6gtlGq0mvu+TZIYgCPH8ACMEliWIKmXCahXLixDCRhcJ/cNteDAKm+UFiw89gR82OexsY47AsWzmmlXmGgHmxBxCFpxeW2C9UaZQgnElY9N10dgEUZXnnn2Geq2MQM3WAvwl6+2VBO9XHfPrmF/H/Drm19t6d5kfx2OQSu7euce59WVKvocxBff2ukwSycVnPkC3n3K4c5dRXyPdEr7jMB6N6U3qTIoMKBgkKQjB0ul1JspgkinSsvCCBnK+TNBYorSwhBEOk/EYowtMMWUSp9jk5OkQx7bQ0p5F+Rq01Ag03b1dbt2+S1h/lP7egFIwh1YpjucSeR62NLgqJ6g0mI7HRH6DaQK4EbGyuLF5yCOnFyk3LVzLoM2seVFgYYBUGSYF3N45YjyOyfo9Nkd95NmHcerLNFYusPPGlzi89woi6SGli7RK+OUFpBcwt7BEkhfYUpE7gkIVSK1me2uEBGGRFQbbFYSuZG2+xP1tF9f38UplCOvsdcdox2KSFCjjopRmNBoynY4QxtCam6fRnqPQEikUFd+h5LvY59pcPDnP7f0Jg0GVtXaV9ZZHzRcY08YWBkdqlLDQmllDo1FYWpFbBmwHWxlso7FsQaYNShQgBAUu2/tHKK0xCL72nRf551/4JsafZ35pnRO//jF0ZtCFYjKJEUKydmIZKQTj3GCHATfeuMGbV/fZ3dgkKocUGuYW12muL9OeL1FebDHqj+gouHt/l817O4wPDnAsKNfLtObaFMIiUYJSrYkTBBipqbZaHFbqJEmBsHKqlYj2XAPXD5iMYjpHQ1SSoPWsZi0ch7AcUG+36Nfa5P37GB0TTw4xKkPYgsnkkL3NOzTaOdVGg/n5OSb9Hmurq5RrAdN4SlTyKAU2kQ3GtplvlAhKJSoLq6zPeXz0hQ/gORKNQvwpJ6efZDDyfnRx/k/pmF/H/Drm1zG/3ta7a3i2BI9fusDG0Yg37h1haU215FJr1tntd0gLxS/+0kf53jcVr710SFCqsrZYY75eYhTHOEojjUUpqPD8hTlOrS/xtVcbbO72sQrNaJihpaTemi0f7B+NyIZdNm9u4zEii8dIDEHgo6VLnrpILdBIjM5BGCbDIdeu3SJaPsXB1oD5Zo3IhWoO2jIYlYNtM5UBW9v7yCoIq43rWCzPt2i3W2wd9FiqNHEDG1EUGD3zedVCkumCUVrQ6Y2ZdrscXH0VYZmZBbvfwI9aSMsnHe1TKDBeSL29RtRcBkdSr1WQwoBRlEtlIt/GlTNb+LzQDJOUo8GIUjki8ixKkcvT5+f59rcEdiVARD71oITlCKQrEbaDh4dtS7J0jDSStRMnCEol+sMJoe9i5RbCZJQdQcsXzIUR4BM6AgdQWjPNFbgO0wJibTNOc6TRlDwX2+TsHPap1+o0IwtpFGiNkZJES3Z7Mbfu3eXb3/wezoNxyy99+ctMRgMsf44nP/xzHPUeJ7JDhpMCbQVYjkWhQecpvSn88NohN+/26HYOUYN9ut0Exw45GE3J8imtxgUWW2Xmdci97S7DwRRyg05itCtoNFdpzDUYTXOKSU48GjMdDqhWAiLfwQ2qzJ9qEIYO1ciiWovoHY3Y3h2xs3sIqqAYxhgj8KMI13cJSyGOF6G0QJCgcx58djZCZ4x3rjDaucrCuWdoLl5g5dQZNBZJnOG7AeVSDWm7xEWBNppW3WP11Ak0ig8+tsSZU0tADlK+UzY41k9Ox/w65tcxv4759bbeVfADMF9x+OQHHuVf/dH3uHx9i97uJivtMhcffQypCrrjhE/98i/TaC3z2quXGXYPufzmFYLQ5alHz3JyoUFoK6Sd4Vs2K/N1rHITlSv2dzvE0xGlmk+lHuHaDoNNH3TCsHMHxyQYx6M/talW27iOhypchChAJBghUMYmzi3u7xyxs7XP6ZV5osCQZAPmmg0MCul79EYxh0cDvGnC3MPr9Hop7XbEsxdWaQZghEIbgTECbYFWBqMAKRjGBXGcMT7cYrh1HSky7mUDUhHhYxP6HmlhIf2IsL3G+mMfoNQ6hTIxJxYrnF6soNME37UxGmzbwhSKJFXc3enz9e++yt/89CehrnEcWKh5NCouWejiV0JaYYlWLaJdhcKALWx8WzDpHWHZkuXlZdIkw3U9HNtGShulNb5j4VJgWzapthgmmqSQTAvBnc09WrWQ5WaD7V7G62/epHu4z2K7gU7GfP3LX+HjP/tJfubjzzBfmtW97+yO+OznvsQPvvcdJqMuvmUhjMESDrbjoQNNVCnx5BOP0BkWvHzlCnalDU5AreSyUHUwecb+UHFze0ihbHwBEx0jVYIxEA8O0FsgnziPb4HvufQjn17niMkwBtsmqgWsn1ojqJYougl7B7t0d7dwKBBLLajXcMOI5sIirguOnjAajrj+1m3iGPJitjxS5hppuUT1BSzbo1q3CKJotthPFQiTzhb9GYOlCtA5hYHh0Tal+gpO2GZrr4PnOWhshPTZPRxjbAc/8LGLAisosb66zAefvEgUOLOsgDZ/5bIwf1k65tcxv475dcwv+HMEP0IXnJor85u/+DH6nT9g680Br926zovf/BJnLj5KZX6V+xu7mFRhS0m30+VbR3364yl3N/f4lU89z5nVFo6EG7e2+crnv4XxqzhhlaODAwZbd9irllk5d4YwqBDaGmkK0AlGT9DkKGMx6OX4YRPLKc02iCgH4YeEjUWEW2I8zRhNUt66s0ejFXBr0ufSWWg1AxZrIaVyCS8MOLz/JotnH0chcF1ByyuYD+wZMPSs4c5YgDIopci1YDDRDAYTxsNDirSLIzO6mwcoLFKrjGMJiiLHkHPizBnOXrqEcUpUXMX55QoLoWAiJChFZlxEAdJY7MeKr3z/Kt/55qv8tU98gp2xZsmyCDyX8+dO0LVraMdlvhKx1AwgHSCFg+u7Mxv46RBVpJw8sU5gG2zPohR6BK5EITGWTZxJNvop1+4ecG+zh8ZDWi7dQZ9yNOTieY+9vR6//69+j/17b+JIjdQFSpQwlXX2iwrPX1xivRXw2pX7FDrgF3/h05w8scR3vvU1vvTFzyEth//lP/zfYpfapDLkqD/l9//wG2zvHBLUmkSVCisrbVaWa8y3mgyVjV2K0OKINMux7Ahp+1h+iTieoIqU4XDCtNAIIalUIxYWWuhCUiq1aLU95hZqJLi4kYdld5F5xnTaI21FpFmJTrdLKgSVkk/VM9y/epPD7R2MBqM0MixRdiV+VKK9co7xNKVUCpCORNgSlEDqHCFAaUCBZbsY2yMqVSiVfaZJweRgiDb6gdGpwHEdhpMMyxZ4tsNgOOXhpTrn1udBK4yZOa3+qffbX/B01tu/7/3a+3PMr2N+HfOLY37x52h4lkJgdMF6M+T/8Pd+nX886fP5z1xFZ30uf+8r2EGZtVMXwbgc7m2zv3OLFz7+cT7ywlOMJ2MuX7/NNNcI2+Nff/6bXH3lNWyvjF9doJj2KY42mWxrevffwgiLfDomHeyASVBGI3SBMApdGJK4T1TyHjip+lh+FYRNt7PP/KlTtBeWGCYZXuywt9Wl3V5Gei673QluEDI3P8+dH36FtL9BrlqoTOFLjWdrEJBqRaIFlpFYpkAj6E8UB92U0eGIdDIGMUsJohW2SDEmR8gIKWdv/kOn13n4zAoxFmWZUw0kni1mjXaFJhEenWGGLQSf/fplXnr5Gvkk5vK1uxz98DZ//cNPcmLJ49LZFV7fOKKQmshymatVYOLQjAKUyekNBiTDEaHjsbgyS0dqGdCJC0JmG3rv7PTY3B+z15vy1lu32d/p4AnwLE2aDknyjLd+WCft7bF7+avI5IACQLpU157ECIvOoODl2x0sq8xzT5zg+UurxJM+w/GUNE4RlosWkt2DPkf3RhyONf3BlOkwxsZBKkUxHTEd+UzTMn65wmQ45NKFE3ha093awY2aGJ3iRSVwfLxyib3DI27c73ByrY0XODTbVSZxyvpag4W2T60acZTalCuShcUW+eEmgxymkzGuX8KWktFoSBTapGlO7+gI8ox8OiEvCshToqpDqVZjfnWN/mQyaw4tCqSUKKNmCysFIK3Zxm/LxnNDSqUKqjAc7h9g+yGYgvGgS5ElOK6L40eUKzW8wCeMXFYXl6iUPLTJkNLGqPfmyem9pmN+HfPrmF8c8+uB3lXwIwRoIWe2BSpjrubwf/o//kNWl2v889/+bfYPdykmR9z84bdwvQjP8wn8Om/88Aq2H/DXf/5jNMsORjjc2j4ki/v4jiGeDPBth3xwhCqmZMmY+KiPMrPUnFBjhJmiAcvMdsQarVGZIZ7aRNUFoqBMYXsIDP2DXQ627lOfX6ZSKgM5xnbZ2D/EuBJHGGxPgu0hBIyO7pNHZfYP+iitUarAdSyUmTUH2sLG0YbMwN3tQ9568wbJ4Q7jzvbMQwOBJQxoBWaWgtRODdezuXjxImdX6oxzhWMKtBCMstlxLNeGG/cH3Lqzy+7WFq/84C2KLEP6Nv/2s5/nILWoVSvMtS9wdqXO6mIV6bvkqSaZpLiBh5YwHMPtG9s4WtJo1XHKNV68ccTGYB9ZrVMpl+nuHrJ9d4eNm9cYbN+gd7hPloyROsN64CbrBTX8sMS4twFxFykFuQZdKHp7dxkMPkM87nHm0z9DveLRsDK0gCIrSPOYJC9A2mgNX/3q95hkIblwqNVbFFlBqVLGcQx+KFhZnScKPWxRcHqxSVgOkcUKVy5fJ7UtkvEhSTzGc6u4QY0khWvXt/BDj9WFBksLLTzXY6EVsDoXMZpMmfSHbO6M2N8+ICkKbMdlcHjEZDBFeiHNpSWqpTKDvXtQKIo0wwiJF1Uwnk+hUxrzyzhBFT3JENiAhRAPmjmNni2spAAMeS4w2BzsblPgI10XMXYQKmN8tEM8GoCwcaM6/ahGe22NtYVVzq3PYUmFBLQxSPneA8d7Ucf8OubXMb+O+fW23mXZyyCMBDPzDdCmwPPh7/693+CpJx/jH/93/w9eefkHGCsnT3tMphZeuaC2vMLRVPHy6zf4a8+co1rSPHKyxvJv/RKvXdvjs5//Op379zAqBQpQE3QxQKsUaRRGZyDUzBvjQWe5wAA5Wk2Ipz0C6TC3eJLYOIwLTZ5lhKUQbIvFhRaNeoUkmdIZjCj7HiEG6ZZwSm26nX3m1j7EMDN044JWyUMIC9u2GA0SxnFOLQqI04K7G4fcvf4m04ObZNMublAmLjTkfWwtsb0I41ZYWnuMRqPK2snTVEOBnGiE7bPVn9A9OuRUu4rnu3zr+5e5/OY90nEf13KQviAe2+xu7VA/8RCjwpCkklagcE2CLSWZ7zIeF1y5uYsShnF/yutvvEWBpra8yq2dEZ/94xcpLZ5k+eE29/b22L16h6O3fkjn5jfJih7ScRCWixvVqLbXqC+dobVwgv7uBle+u4ORghyDsMChQOf7mKLP0e0I1b1EzV4itA1xIchkyNHoiP3DHpocKQ2DfgfpLeGH0ewGsW0KoykHLk89+RgXLp5H2oZGySOybVIEuVHUFurodp3dexl59wgjBF6lytnzp2g3y4yGA9KKz/J8g3JgU/MLFqs+cxWPpaUl2rUBryjNdpaAZ5PubJKMj5jkHSwpZo6xkyl5UWD7EbYfUWvNIz2Pye5Nas0aSrgYHJKkQAoH2/LQWCA0QpjZ7iajQc8WWQqVk436YAsKrSmSMWo6wuQ5wnIRfgnftVlZXqBZkiw1Q6SZTZW8vQHnvYmP95qO+XXMr2N+HfNrpneX+UEgDWhhHqwsE7Ptuhgef+Ii/90//r/zhc99ji984XO89eZVkriAyYCN179NHvc5t+wwjJv4bhnXt6iFmksPzXHz7jp7G1dR+QStUkw+BgzSGKQBg8SY2RKX2dK0tx20FaqYomJJrgzioMrpxz5IWbjYXkCj1aTQOQpoln02R4eM0oJdx2Xeslk/c5a7V07S373BhVqAU62zO8443Q7QamY+Jm2XGzv7hGHOoDfi9Teu07l3hXS4QZFOqMydJSrNMz7copgc4tdbJLbPhec+QTkQlKt1jDJoIYmTgiu39nnz2n2eOjXP+uoC2/s9isKiXK6SZyOMgvnFRQau4IPPP82HHz9LKbCxpEAYlyzTTIziztGUt/Zidre2KRHT6+2TU2DsgM/94RfZ2e5xpr5M72iEtCVBuUypPcewt0yj/hAXLz3K+vpJGu053GqdiXC5cWuDa2+9TpGOCEwO0kUbG4TB831s20UUisnhEelU4VR8DiZdXnrjgJdfuk7ncIqUDlJotLAxwsZ3I/xyFb9UJqpGnH5onRPnTuI6UC17NCIXTwi6saHdiPi1X/ggo1jxne8H3HnrKmGpjBMJ1lcqnDqxQJoVVFyHNM0Q+YClxTrz1QAsizg1WMtluodlBsOI1J49YkweYytBMuhhmlXyPKfSarGwsIRXaxOWm6RZypEeUW+UUMJBG0m/N2YySRDIdxb1GaNn/iHGQkobKWyENiSTEZrZSVIXBbbl4Doh2B5eucbSyRPMz9VZagoakYtEoY18QI0/Gz7+Krsz/zh0zK9jfh3z65hfb+vd9fwAWmiMMCghZuljI2fpLwqqZZff+M1f46//yi/x8suv8dk//Awvvvgq/f6Azp0rfG7nOgc3nuXTv/RpTp46jSWg6Wmeeuw8g1HK/Vu3iAc9+rsF5AmSmaW3MQIjBOZB1CqQsyYrY0AXGJFgWyVUOmZ7a4OVh59gZWWJyJMYy8U2BYvNOsZk3Ns7YhInCEtw4swJzlx4jO/fu4ZKB9j2OrGxyZQmkBKjFIUWbB6OOOrvMjjssbfbQUw6MNrDNlMG4z7zK0/Trq6wv3ud1UsXGYwSwnqd5TmfclRimkI/hd3dA/rDBGVFDOIUYQnW1pdxrC7nHmpR9Tx6nQMsK6Z7eMgv/ewHOLMc4NsZRmmUdlCpAlEQ+RaOJZgOB1x6aIHvjrsIbSMKxevf/gJhrUU8uog3bvHYI6usPbmGTp7i3r3nWGhVOLm6yFw9xJWaXMMoF0Q6Y3uhTc/3MVmIcMrMLyzxwQ88w/Mfepb5uRZeuUZvmNBLCr771ibf+tZL7GwfMR72mE4mSKPRCNxSlcrcOqXWHGGjzvzyEo5jOHFymVY1oB36hIHAswpC16GQgvNuhXlf0k0MhXmcwkCtGrCy2ObCahthcuI8J1GG4XBA72ifuUfXKLIUYXvUA0HkOmSPrHMwHLO1bcCySdMYaTkEnoNtSRrtNq2LF5hfXMYNS+TGYTIa4o7n8SMLN4xASEajAZPJCKUVoDFoMMWDB6c9W2JpWRhpMCJHqwQpLEBiWQGWG+GUqgT1OkG5TFHEPPLQRTzLYLQELED9eO/oY/2pOubXMb+O+XXMr7f1rqe9Zk6OM3DM4jjB2+coHiTCosDjYx/9EB/9yAfY2d3nq1/5Ov/2j/8d127c48Uf3uNO57N85BMf5ePPXaLkOZxdCAg++QR3L5zh7v093viuQ+f2CCGmCJMzw5ONMnr2G4V8J9YURiKFRAoHI32EE2KkZL5Z4uHVKqN4RLenWWh4LNcX8R2H3d6EwHOo+C5PP/cM1958iTwekxzucX83ZLIYUrElYwWbvYxud0p/v8P+xiZMO+TJmKKYdc6TdhAioX7ySbLA5YmPfgQv9LCsgMVygetZbI8Ul2922N/eoNls8shDK5TNgHZo+IVn1zg81eLkaonQsej3y+weHpIuNjgxH1L2DAZJklv0pwVSGEo+XJgPKVvLfOrxJe5efR1daKTrce/OLUQ+JD0csHf7FR554nEuLVc5PR/gWxYfOf8ktiXQQqMKTR5PiXwXz3JZblZotxfZWbjEyZUWn/jE83ziw0+x0KggpaLAsD9MuX97n7du3WBnZ8C1azsU4yHS0WgkjnZQQrJ0+hzrj38QLww4sdZmZaGOKwTNSkjFl3gYrAeOsJk2CC1o+5KyM3tIPXGqykL1SWzboRk6VH3BwTRDqQJlu/SPdnn45CpZoZC2pBFKyo4mKQqW6j5nllsIBP2tOY52dymFIZVWneZ8Hc+3WF1bpVJvoIVDrmxCV1LU6wzzhP5wTDHJkdqgstFsGgeJsGabizEKIQWaAmkMRZZhS5CWReBVkU4Jyy0T1po4lSpO6BGELlU758RKHWMKjLFBPriejXzPLAN8r+uYX8f8OubXMb/gzzPq/g4y3vnBf/RTM/syCikEK8uL/J3f+lv82q/9KrfubvP61TscjWMsz+PW5tHsQy2XqUQexnTY3rpHvVEj6zYY98foLH+nTjn7/vYimVn6ThiJMBoJWG6A65fwvZCjTo+9+z6rpxY47Gyj0oR2zWGxFTFMC3qDAfOtCo89dZqrb32A7iTm7KkVSuUSndGUihuxO9bc2hvT70/pbe0w2NuhGHXAQBS1iKc9pFKk4y7Clpy59Bj1uTbnVtsMBilVO6EXK7YHMddu36Pupnz0yRNEnkfad1iILJySx+nFCF/MDMzsTKDLPo5bJnQMUhsKJVHGYvNwwNUbt/n4sw8xX7KJGj6Z0FwbdbF0jlSG6SBFCB8RlMFy6W7foswqrnCQjkVRGMZxQa4LbCmphiUsC6ZTRW/Yp9EM+N/9o3/IUxdPMtcIsCmIC8VgUvDy69f4wWs32O5mZCLEsQKq7VWYM/iBZLLvMt0cYlTB+dPLPPfcOeaqIcKW+L6PbQCV43oO9qz9k7iwmAw0eWEI6xYphlGqCR3JxfUqSgkCCb4LhWNR4JKnGa5JObXUxLMFpZKH7wgUBqMNahpTL5WIKgVRvcb86gkqtQrthQXm5lrUqgHNRgUcybgAZTSO5+JXKuzuTEn3O0wPOuSjDnkyQKsMy3IwGgqlZmlkBNoohDF4jkehFHleYDuSwCvh1RqU2/OIMKJSCyhFgqceXiVyLcAgpMCgHzBDvOvC+X9quuLHkVJ+L05v/Fl0zK9jfh3z65hf8OcIft7NLzVmtktGSvB8i0sPn+biww8xzQsOej1ubRzy4vdf4603Xmduocn86joi7nD32jWKaRfL8pC2QBcJQiikmV1ws7K5eQcq2uSoPKWY9siHR1x95WV2qlV6W8tcGp/l9LlV4lGKVY2oRhZhWDCaTugNhyzUIz743BN8+ds/4MxKg5X5OqFvGOcFca7Z2t5jb3uPyfZ9ku4WphgidYbrB+RZhu2VSDON7zvUWy0i36PpCowHWjjc2p9yvxPjuDZLLZe5yMXGkAcuQkoMBluo2SlMaBxHEziKcqVCoRWjRONaDsIBvxKyN074v/73/4a//Qsf49z6PNoolleW+a//4X/BZz//R1y7sYkTVDj//Cd58oMv8NRDa5xcme3FeWtjSJwJkjgjLHmstCJ8A26R4wqLR08v8LHHlolcgUCTF5qNo4TL94946fI9trf3mYxztBVQn1ui3W5RaTbwqiU8u+DgrSm3d66DLqg4mrWqRxgFxCpHqQzHcfAcGw+BbVlMckOqIEYyzAx6oKgFkkEscYSi5go830bnisCSNAKJzA3Xt7eZa9XJhcNRL0YMMwTQqIZ4toPlClwvQ2ExHsX4YRUsB9t2CMMQz/MotMFzfNI4ZjLKCFwHP4wQQjLqHTE83GW0dw2VjBAqw3NcNA5og9L57Do3GmMUptAIqdF5hpAS6XuU6k2cKMIOfSpln3YVHj23ggPAbBIHqR48/N7OSBzrL1vH/Drm1zG//mrw68ce/Lytd6I3IcAILCFn6TYBJQei+SqL7SZr7Tqfy/r88R9/lq//8YCV5VMsVhw6hY0QLsoKSab9B7Xy2WsZeAAQgRQSBTNTruE+PSWRpTmOpgOyyYiN7S0+/dc/wac+eI6kyLEdiyiURGGJqutR0vDQ2gLftQrabkbbU3hyNvp5sh3xzLlFdm/d52DcJx9sYooBpkjJhEZ6IZW1R9DRMiovIItZqvgElsZ1NIfjlPtHY/YPU8gz6lEdgZilv61Z42OhBEVqcDyJzjWWFgilMdpwNEgJwgBp2UyTnPm6zV97/lF+5+49/i//t3/CY08+wrNPXiAyCW7JpbqwSHrngGefeZbf+vu/RbVWYq4SMi4Eb26M+dK3rjAcxlRqNVoLDUYnNFnTZqlsUw4tqmGIbwqSImEQp4wTwyiXaLeKiKo8+twJAsti/6BDVK1w/vwpJqMWucrxLHhr0Oa24+BIQygNc4EmChUT7dCZ5IzijBvbHYQpyJIM4ficOrtOAez1Bnzv6lVqfsS5Cw+x2vaIfNDaUKgcy1g42PSnOS+9cYv1tVX+8PP/jLfeeB2dZ2AMZx46z6/8zV9j/cQKuclxHZtSqcFBfxPpO4SlEmmhmXRHpPs9Fpcd7t7f5nDviJWVJRbKZYq0IJvGTIY9pv0BFArBzEJfSgvPn23LVkY9eIApJDmT8QDHc3EciywrSPOCiutSijwqvuDEfIVmxUECxkiE0LNyy4ND07F+unTMr2N+HfPr/c2vn1jw86MTlHywWE+/0xk+q3grQktxfr3Bhf/mH/Bbf+vn+eIff5l/85kvMh4eUi0HSCfC9aocHGwznXSwVIHWxYPXloBBCwcsG2P7WI6PbUuicoXUtgjbDUqlFnfud7nS2uPCuQUGkyEL9QBdKJwip+a7lJyIpy+cICqGrJUXsKRE5wJbZDx1qs7diyc4urvGxs7rmGyIBlQGwm9QW30IK2gRD3oE8wELkY3jCGxr9m+0dUZZFjhln+Zci35umIzG1D2BLQT9UcYkEcyVPYSWjEY5+90JZRMyVgWVOZ9xMuX+9h4qHfHE+VP85m/8IheuPMS9vSNubA8o57ucXoyoLZ3ixAWLT37q53j0xBwIxUTB7YOEV97aYXv7iGl/SPdgSLc/xfddSUGJGAABAABJREFU6lGdetklSxSTyRSpNJ5dUIp8KmWPWiGwQ0WzeZFy4FF2LfJ8iUkSMz/vInQLu9AYJGJvie/aBqUyQq+gEYKRBf1M89L3X+MrX/wCd25cI9GSzCrz9Md+iRfyCp37t/jWv/0Djnbv01w6wz9Y/UeYljsbCRYzMy6DJM01P3jxdd68fJNvf/Mlhp1d0qNNRDZCFRnf37pNoQy/8ht/h8IN8W1Dvd1kPB7QmqujjGAwSYmzjNFoyu7+m9y+cYeSGxF4AR4lMmXhlaqU603ivZnBl8k0eZ6Qa4UlNJbjoPJZ2rgoUibjA4oixhIhKp0inJx4MiGNp0S+wcng0smzOFKjzY+uXWHkg3vkPbgY532uY34d8+uYX+9vfv3Egp+3Jf6DuFDwo3dJgjEICcYULC8v8ff/3n/Fr/36r/P1r36Vf/n//T3ubh5iBzX8Up0ki5EiQRTZzKX1Qekc6aGETVRqE1bXmOYKvzFPrdlm+dQaRmlWT65zfWtAYUtOrjVxlSEohWzv7RFnLrUo4NTSHPmkT2TluLbLWAmKXLNQEjx5aY2rb55m+60WuncERoEAXWQ4liQbHNDvbBJdXKTkWUhhMFnMWqvCaqvFYJCSpQl5Ifk3n/86tiV57qlHUUXB4STnqDuk5NuMJwMmkwGR71DLHGJtY48Mnf0jcmNz6ewJbCekFsKvfPIpdo/G/LtvvIqjwRHwyMMPc+bc4zz88GksXVAIi51BzuW7Q+5u7ZFOJ+g8IUlzpvGU82fbOLJGOk2JJxOMUCzUI9rlCFsYjAW+L3Bdl7W2B7nCtwyW5ZEWEscGUcxs6HuTAolGqRylCwotiDPJZDjht//H3+Nf//7vk04HuG5EbfEc7VPPMM0dfu93f5/u9e8x3b2MRcqhSun3DlHrdfJCY9sC27aJFdza7PCtb36Hxx5/nOr8KghJb+ce925d5a3XXiHr7/PWD1/l7CNPc+rSB5AYolqJxfUV2o0qrisRjkUynEJecP/WDfRoyFGcM+zvMF1fZjROqC6sY88v0LvnY3SMslzQs4eeVgkCjWXbWLioPEOZKRYZKpMk4xGl8jy+Z8/6AvIpjTBiba4K4u27QTM7L80eo7PCuXgv8uN9r2N+HfPrmF/vT379xIMfzKy2bTCYd048AAKjLYwUiFnTPAJBrRrxq7/6C3zqU5/guy9d5nN//G02tg4Q5EwGRyghcSwLpEVeKAwzEyekx9zaI3QmA3RQwis3sf2ApXaJpeUSuYrY3N2lWo44v1DCGEWpWmWrO8SyJI1Gjds3dynyBF8KLMthvxszZwsuLJe5eOk8t36wyHBwF6ETpBuQpymHd99g1OvjOtYDqAh8W+BhWKyElCOfcdVj91DwB5/5Mp/73B+xcPIEdlDlsNtj2B9x583LLJ44hV9v4Pk2a/MB/WFKqVoGZTh/chWtJUm/Tz+wUCWfrMiZr4f8wocf4+YPv4vDlIunTiH8BmHJp58U9HPN1e0+RxOFMgLHC/DcALSiNVfj3HKVdghl16LhVymFAt9W2MYgbYtCCHyh8Z2CAhthCyyh0cLgOS5ZPrNML1ybqYHDwRQsB2n7fOs7b/DG5Xtsbt5h4+5thBGcuvA0H/+lv8Glxx9lEAf8D7/zBbrXf0Bx8Aa2HlIA+aTHvXt3efqJMwgxu0CNhEFsuHpnm6eevMSHPvY8B+MC17U5/ZFTmPh5Xv3hx/g3v/8Fblx5la2dbebOJCAsqpUalUoF1zJkWcxg0EdlGQf379G5e5Mi7mMJB0fXGVY9xsMcJXzUuM90OjOUM6bAkbPR0CJz0CrBaHAdG0lMUUwQRiOERqtk1sQYBtg2+LbmkXMnKPmzzcczQugHSQSBno38IN+rueP3u475dcyvY369L/n1Ew9+DA9OOOLt4uCP3iUhDOJBbX02Y1EgxWzgNAh9/trHP8iHP/gsd+/v8/XvvMRXvvV9bt+8SZGmGGwcN8coge1USNKEbm+X2vo5zj/+GEHkkiQTPN/DkzY1F/JqnWubB1QDl8WKR8m1SVyfy9s9GmGF3ihnHKdEXoAnBVOj6MUFTV/y+MNL/LtKhZHtoh8YjwmT0bv7PbQRuPNnGU1jeuOERimiUQqp2ppA5uDluCLnyve+ih7cwSRNvv/177N954ek/V3yNMUkE5pnnsCrBewx4fTqEuXARSkIXJcwsEiiGqNUoYWiq1IyLSkHLp4rKYU1GlGIcn1i7bLTT7i+d8S1W9ucOXGGdr2Mq6Fa8VlYqHHh9Bxn2iHb97f4+sYRTz1yhidOVrClhSUEQuYIYyMNSKGwhcCg0AYy47DXS+l0Y5JCMEi7jMaGb37nMnme4wnF9Suvko6P0NJBOzUW1s/wK3/77/Lch57F9Sy2egX1isd+OsbkY+SD7dCqSNje3MJCYzsWtoRpChu7RziW4ekXnuXeYcztjS61yGKlscypls/chy9QrpX4H/8ZvPn6FSy/SWN+jcF4gus7kKf0ez0s16G7d8Dh7gFRpQm1NifPniOTgvZcm6OXX6Y43GKwfw816mBXT5AbiUyHWHaNXPgIHSO1wXEcSCTGzEZYEQqlJphkQhFPMRWPeujy0IklkHJ2rRt45wEqBFK8V/1R/2romF/H/Drm1/uTXz/5zI94548/Qf/eQjTxo//rbft3ozICV3L+zAKnzvwqn/q5j/K1b3yPP/g3/5btgz65MQht0WguM4lTup1tSq0mJSunVq4x9jzcsMI41zi2RRjMxv36/S6B3aSXKPYHcG9vii8mHOxNuLfbw/HKRJ4h9Hxu7fR46swCJ5oRzWrEtihAZzjKAtuaNY6pAjXtcbC/zUF/wkq7Olv6p1IK7bA7VNzeOuCou4/MYqa7t9m/9SbxeBdP5jhOBduxcEXK02fWWWnahL6P5RQ0l9tE1RBbCiaJS+coYTyJOTjqs717xNpcmU7qc/X+Jp9cfARdOHTHOXeOMq7eOaDkRVQih5UnTxFoTSV0aTVsUAVf+OK/4wuf+SzTaca9j3yc6H/+y5xbreFRzGzPzcwRFFsgpAZtyJTDtXsD/vUffoNXXnoNPyghozq1Rp1bt27iaYUyxcz+3Gi8yhyPfeSXOXvhUZ585ilqkUVcGMZxis5HiGKEMRItNNqkBHaFyKuQpzlSWEgMeZKSpSlnLzzERj/mxmaHrc0e+7amHgkql5ZphBYPn1nkb/3G3+APPvMlfvCVL6HjKdPpIdI22E5Eub3Kw899iEJIVh66RFCuUi0HPProJXqjLvub98kHHbr7GxTTQ7ROkbZNWCnR3e0ThT5+qY4jNChF5NkMDrdQk+ztDg6M0RTZFJNNEbnHicUFGrUI9ANP4f/J/SD+g2//kzvkzzH2+dPmpPqe1jG/jvl1zK/3Jb9+8sHPn0PGzGbnBBKBQZLjSsPaYpX/4m9/mg8//wz/8g++xCuXb3DUz3CiFrW6jxmMONzd4muf+dfMrZ+ifeIs1coFRmmBLV0ix6LVrhKQ0R30udOJubc15Pa9bZLpBNHdYKHuEDUXWXVDIs8iNoKDOMWWDqVyA0t4aD1BFwpjWSgU0iTEgz3u37zGjftPMb/cZK+XcXWzi/SavPiDN7hx7TWilUsYf5lB5wbFaBO3yJGOQGuFEwacOzHHhx9dpewVHBxNKKSZmVcNR1TKIbWyQzsqkRcafbLMJNVM4oLlM49QXjzF3V5GoXOM9PAdeP7iCiuNCq16SLVk4StNnFtcv7/Dv/j//A+8+N2vUBR9pLb5/L/eZzwd8qlPfZzzJxdxyxEHO7s8cmaBsmWwFGjtsrM/5P/9T3+f737vVfLhAbJIwK2RFhm10GJpvsXD51b52te/ziiVNJbP8qlf/mVOnVqkHhoiXzMewubmAfduvkk62Z2ZZRkbsIlaJ9gbFVy71+Hk3CqOleNIw/xCi+t7I+7uThlNNHlmULnhzt6E+XbMqeZsBPfk+jq//Dd+jRMnr/Ha97/L/naGbRsW189y/onnOH3xEtM4YRRnjDLDUqtBULaptuaQ6YB80iXtbyD0CIHCsiwUPtKN8EpVRHkeaSTpdICSmqBWUJicdGqQRs2s4tMRhpxK6LOy2MK1zAO4HOuvgo75dcyvY3799OunMvgBMA8cIxWAkBitkQKkMJxabfLf/K//Z1y5uclXv/NDdns524cx0/EAMeox3O1i0ilC2vSX58lrEVmesVr2qDUrkAwZjxM27u+wdfeAg7u3GQ5HWOMDLnsJrfNPUtgRcz4stZpsd4coXGSpje/WSOIjMAVSFQgBBR6WLDHpjbh1e5OFtRNcefU6L//wBhAw2rhCOYr5tf/Vf8v9jTEv/dE/497Lt7EBZYWUaitceOgsH3n2PPMVwXSaMxhNsAIbIRX1skO95DDNNd1uH8/zKPsuxkxwXI/afJ0kL5EkU5LpFFsqMiVptOaZq7qEjiESBVIbjqbw8t0ph2kZtMRVMUo7CAZ89XP/gm986Q9p1OtUF9fJJor/8jf/Br/8i88TepJUGw4Tw7lnniOL2kw6B7g65ZELq7g2dHY69PZucP78SX7w0ktEoszPf/rXeWhtgbWWhW3lJGlBnlqErs/i4hI37s22VjtFgcInaC2weuY0c/MtbGvWcKqAnaMxr755l439jCJT6FSD69IZZNzYHYHxONkMqJU8lhfrTM0lKLcYHn6Q+bkya6fWkLZFsxbi2LB1OODO/gAtFZNkTBhVmJuropMBJh8hxRRpLEBTCBfpVbCDEnaljeOV8eIh6egA2zJUpSHxHCbDDtJolC5QAvzQp9GovmOYp9+j6eFjvXsd8+uYX8f8+unWT2fwI2ZjluadCTqJeNBpLjTYaEJb8czDa5xan+PG9iFf+8FbfH33PikFXhRSGMF0MmV/Z4+WWCa2bTxtCHxBxXEYxxOU0mzduc5g6yZ5lhEIuH7zDs0724zxeXa1SsMLGCUeN3d6FEKgpIWxLLB9LOmjpc/yyccJynPg2NzbGzL90g9oeIrnnn2Ut67dYat7iycffZRnHllkqZ0zvHmezVd8tEjAr3Hy4Wf4yLOPcnqxgiUSEuNx4+4+yyszsyzXsUm05vZhzDdf2aRarrBz402uX36d1vwyXljDCwJuXL3M7p1rkE5Yv/AYz/zML3HmzBLzFZvTcxGhZ9BOQXWhwrkPfpDxYJf9t1IsErTOMSbFjCd0x7t09u4S+G3+6e/+IXatzc88d5ZaKDm7VKXRqvCRJ08QyNlW41rJQWAYD3Ne/sE36Ozfo71whsfOfoBf+PQLNCObpm0wlo0UFrWS4dKFeSq/9Rv8niq49tpX0KNNLNvB9zzOrzc4uxTgoYgzzf5Acfn6NjtbPbp7Q5LphNALEK5HWgREoYUjqpSDgHakadZsplaFozjB9mxWV+YISza6mBI5hmmekwtJqiW7RxNGcUphDFXHxQlcLCmg0Agh0VrRWjsBUmIsB69UxgoaVJpV4p7NcDcFy8N2fFzXJ09GaATtdovTJxZYmm9iWRYo9Z8pofwpt8Kf4lT6Z00H/8d//7gM9hegY34d8+uYX7Nb4aeYXz+dwY95kDA2b4+Wzt6Ad/4UAkEOOqcZ2jx5eg7PFNhZRqc7ZqMzZkoFKT1G+weQ5rQW5igtnaBwbJQtcLyMcslDFWP6h3dwTEGhLcRUkGVTBtOEzNTxyKl4gtMLLfQzF3n9a2VE1iZsrGP7JRZW13jswz9Ls94kHvcYFQY7H/PxJ0+wvLTIG4+c4Y/8MY9dWuVUzWc+8Hh1robxmwihOfXwC3zi536WcyfmiFybfupzffuQN67vUCuXKMYDpFWlwCJWAhm1eO2NN/nWZ34HNTrEtiMWVk8wTQt6nUMCmRMP9hhOx4xEnTdunsI1Uz789Hk++fxpmqHF06fLrLfO0C7/Tb7+OZfNV76GzQSNh9T5bOt1MaHIfPppzsiAcSXC0pSkIbRt1qMIV2jQGmFyhCwQvqHdKrO3m/Hxn/skZ5/8JH4oiUKJJTVaCDwbKr5BupJatIj9d3+L3wWuvvJ1hG1z4eLDPHJ+BQdDkhs6E8lrt3b5znde5WingyokcZaShyGuH+CbKv19n21pWJirISxB4HvkBUymGQe9EfMLLYrJFN9WpIVh93DMdi8mnhT0u0MGrkUyTZiLJFFtjoHbwBgbKabYrsPiydMUCHrdfZqVgEJaVBp1FufLXJ8cMol7ICzyPEc6FtVag2rkcn6lynzVxygDcmYLf6y/Ajrm1zG/jvn1U6+/9ODnT43kjMWfGGUKg57NKgCzvnNfwJPn1jm/usDGQZcrmwO++uJtbt/aJekoxocHlMoekyxmuBcz9T1OtKpUL55kuPMIRxuvMz7YxNYG17Z4eLHE0nqLcujjklJyJVlasL7UpLl6jrgyz8qZR5GhzwvPP8LTT14gFIYsbuD4EZ7JKFsTmiWDd34B23yS+aqDIyS+LVg6dYbTz/0cvhPy4Q9/hMcfO00lFGC5XL69xxe//BJ7BwP6wzFC5VCkWK6kHvjEvSNuX72GKx0ypUCP2bjxJkY6LK2eRqBJxh2YHjDdv8lerghLPgYJuaYR2VRaAeOqw1zpIchTfuet76MnfYSxZ7t/pZhZOWhJu71EtVRFPmgglAYszDtI11IihIXWgDTYXoQfhCiTU286TFNF3xJo10Jrg2WBLman35ov+ODTS3j2b/IH7Rbaslk99xC+6xAXhjgX3Nyf8vr1TQ4PDpn0jsAOqTQeOM3mGeQ5eZwymSj2BppRnNBuebxxbZvrN+5TbdbYHYzwXGiVfUw/ZWt/yHCqmA6mZMMhiS7IYp+84iL8GpXVS7TbNbZvfIv2fIuT58+gLQtn2+bShbMMC4lnW3hmSlCKGB9YCGFjjEBrie+7zDcCnriwikOGFs4Df1/9HnTDONZ/Ssf8OubXMb/em/pLD37+NL0zQPon8ePf6zCfWWwLMDmRD2dWG0hLsHvPYu96l+1Oj+b8MtM0oT+NKUceSJ9q6BIEPh9/4Vn2d3b45h9/BrsYUiQTgviIhQA8obGEQ8m10RULLJuf/flf5P5uh0Z7Ab8Ssb7a5GzdhjQhsS3KJUGeGHRhIYWg5hScmQuZWiE/3B5Tj0Layyv84m/+FlILTiyWaUQeQiSkWFy7vc/dm/fxbcM4Tkiygn4cUw99PCtnqVXi0qMXUedPEI+7pHnBaDRm2O0S1Vp4rsv+zj1Mss/+3R9yqhzx65/+Ozx7aZ25kosrCoxRBK4hmnfZOTmHtgWIBIGDYbbx2tE2ttfAD6t0DrsURRvhSYyU5AUoA0IKkOBisPTsA7HdgDSFMIrAWOyMMw6GGZ7nsXFvm3OnFyiXAtJcYycFC1WHpx9ZYW75N4kLC1MIhDEMJoreJOXaxj69UUytvYBrhxQaolIZKSRxkqKNQKmCLM/p9EbsZjHdiebNq/cYdocEYcBwPMJ3JI5RJE7OcDRlPM5IpilCa1SSMhEaS+SUmm3OXXqStXOn+e7vD6gEIXPzDeJcobIxJdei3CjjuR5W4bE7N09/ZwuhQoJynTQeIcg5f3qRRjkEkc2mKIRE/BQswDmeBPuL0TG/jvl1zK8fv36c/PqpDX7+0wHmn0QUAWLm63BmZZHqz5fIxn2++OVtpBpTjI8gWUD6FqPRgGniEgaCZqPOE08/zc3rVzm4/ga+LegcDVjLwHUgdA2erWk5hloY8vwHHqF0Y4NKOaRSLnGiHRJahkxqIkfgSyikxIiZ+6U0Bil8bm9NefP+Fks1n/On5lmaryGUwBYKzzIgbYZxxtGgP/vnGJBGoMzsdXRR4AvBqeUSjep5KtUK4yRnqzsiz2fNi5NJisoFg4Mdtt/8OrqY0q47PHVxkdWWg0MGGozU2AZcoZiMexjpICwfk8eAQGqDEB7GcShVQh4+MU/Vd0BocmPYH8Xk+KRKIiRUfQgtG4VkSsiV+z0WVht4e1Nu7Y+wbIdcumxtD+iLkLVFie86OEbjebNJgmYjYDDOcKVFbgQ7B2M2tvfZOxoj3TKVuotOBVkak06nAISlEloK0jQhmybs3t1nPB1zPd8gHsYIDSo3qEKSKUVqK4osYTgYksY5yTjGsT0sHBzp47ouc8uLnDx7krVTa1yfW6LkO7iOQ7VaZtxqooyhEnh4jqTi11lbX+P+tWsU6YR6e4VBv4Prupw/tYolAW0hhHzHD+ZYf0V0zK9jfh3z66da7zr4+fejrT/L2vi/OBm01thy5gExX/P43/xXv8qjF0/zO//yi/TuX2HYiliZf5oskwwnE+YiH8eyCKstaqtn6O92yEZ7XLm1TVK/yeLCEhdWKqxWLWq2RluKwNVUqj7NepmyI2lFFo405AKQNoWSTDOD1oZQa7QyZEpzNC64cvOADTXhzEKNWs3HCjzSwuA4YHRBbzJm+dQ6N+91GO1t0qyXAYMlLMgUjTDAXyghndmel+4opRkIXFswX4sYTwtu7kxxfulv8aV0ytb92+zuDciTBIsQKQ3agJEGjI0QktPrS3z4o5/i+huv0Nm5hUoHSGGD5dOaa/LxD17k6bNtAmkoDMSFZmocDiaw0xkxnUypVhwa1QgQHI5dTjzzc1hexFv3u1y5fJsgimisrGIFVbqxRu2NqFRDHFGgLXt28sFie+8IR0oGgwl5VqCMxI3qMOyTZAnSCXCNYjIckqUJtmvjBj7T8QSwOOrcJyxXKJQCXeDZNrooSCcJxgbleQwGPfqHR6TThOl4TBSWABs/cAk8n1JjkVqzCoDGpZA2k3iKEZqoWqUQgrxIiXyfwLexHZtSrcU4S7FMQqkuWV2ZZ32xidAKg/UgAfB2FuCn6Z75q6djfh3z65hfx/yCn+bMz7uUeFDLRc3q6UIafGn42Q8/yWMPnePzX/4er925wVtC44Z1lkprCGPjAqHnUG208Ko1inTA7TsbJMEtNjo5lnuGSlSnETooZdCmwHUsvMBFZlMCK8AWoFWBsGzSQjONc1zPQhnIVQ5CceLEPGu7GQd373F9s0chHfJixN379/jkMw9R9QVhEDE3P0+51Sab9JhrVREYkrygGoYEtsCzFI5VkBYaNxQslEvYMie0EpQPFT9iob7Oqfbf5wfff4nJeEQ6zRF6lmJXZvYlLAsp4JHTC/yf/9t/wIuX7/LlL3+FZDyi053QPdzj1//mr/DLP/M4JTdHYMiUTWJmVvDX7u7z6us3MNogJZQin3K1Sr3dQEYLTNKcrY0tksMRo90Dxr0BfrOBqldIKiUKbCwKlHLIC0OiNRtbU4okxeQJYehSqVSQlkLaNo7vIXWEsjVploJlQGiCMGDaHzCdTEjGI7JpjBf4YHKE4xD3bZKJQ+T77I+G9LuHdPb3IM/QWYKJB6QFSEfQVGUs2yPOCuw4R4YVClkwmo6xbA9hW6RKYyUJ840SjiMxAsJagzyeko8OsSybcydXqUYes8aDmdfLrBDy/gHHsX68OubXMb+O+fUXq/dN8AMgjMBg0D/6CbZQLLRC/su//fN8YHOXb71yjX7apewsIoqYkuvyyHoTPvY8o+277GRDDrY2Qb5OK7fZXGyx3K5hGwulC4bTgpLjITUIoXA8m6xQ6EIjyJG2pBR52JbAtizSNMW3NcuR5NRKQDwucftowht3XmPUn+D5hvNrC5RXmziAlUxZXWyz3vJYXmjgWIJJnJFVNUpoHMvCESBdieuAxWwfj5AOBmiHhqrvcnH9HM88soJW0K54WKKY7WLRcmbWKQyWpShL8JoO7rOn+MBTJ0kLeOv2Pgc79/n0Rx+jEQoEs9060wJuH2a8dO2Ay5fvsLu5g2NbWEh20TTnm0yygsD32bp1l+3b95j0hsSjPuGgSzhoEzcbDMplBA62a3PYPSQolUnSlOk4JR+PkWik0QR+SKEUbuCRBAkGFzeoUgiN0NFse7UxBGGEZdtIqQhsSTYdoDDEI0UaT5C2xcS2cWzJYNgni6cU8QhRpCRCQlQhLRKmcUxZeyS5wc4FfrnJuL+HZVn4no0QgmSa4voOxoBSCuk4uGGEF0ZY+ZjR4R6PXDiFbYPW4kFjpZntwOH9ho9j/Th1zK9jfh3z6y9O75vgxzzwUgUNQgESowXqQZe6RcqFtSanll7g7m6XLBmTjjPCsEzVESw3IpqtOW5fewuZFxzdu8J0mhN5kjxNOL26hO9JBuMpK7UyRa5IjWB7kGArjYdNybdxbEMJwGiEFuhc4wvDcsul/sIqcyWbly/f5/7dTQKvxMMXL+BHAZZrE5iCx04ukGUZvl8lDARSCUyhKfKCQhtsITFSgNCzWroBC5DYGCHwbI1jDLYoCGrubJGiLBCiQGmHTDsUGhxHY5lZXO9QsFi2sBSkWDQfXcR5fJGSbXAwGOGQGcMwg8v3+rz45hbTQUIUhKSTIcJ2icol/FLIKJ4ynCRsbe6RjScU+QApMkyekY7GSAMHmxtMu0OUdLB9jzMXL5BmMbubG4hJjBeFdPanpHmGHVUQjkPUqCB1CReB5dkIXaDSjDTNEQ/2y7iuRX9/G9cPsMPybI/PeITRBZltYdnWbJmfYzOdFqSTIV7UoNqao9pq43geSZYzzRX5OJ75X7gBrmVTDUPSUs7e9h2m0wn1yMOVZaJyGT+KGM4K5NRLLg+fO4E2CiPsBw8Z/adfuMc6Fsf8OubXMb/+ovX/V/Dz5+22/s/V2v+8r2sED+qTb4eps++zwUaDxOBbcH61SZpGDAdDsmSI7XiUXIcLFx7i8pUrZN1d0t4BRhXceClnd2uTydPP055rUgkFnitIsoztoyG37u6wUPE5t9qmXPNBmFmzYBFTKJu4yPEti6o9u7ifPD3HtWubNJpzrK00+MCjyyw3QrTSVEKJVobzazVsW+DLlCLNEdIQZzlNDdKSaASFMUyUQUoHVxg8AVKCRGJJEEZjId62FcEIiRIWUyXINbhaEj5YxSulwMIgBQhjsFwwRmMLMzuNaoPSknFmGMQF7bk6/kKdIp5AkWMZi0kWI10bZXm4lg/Cmp0ssLF8GyEtpIQ8jZn0ehTTHOFE1JcW6Hf2OejsMjzs0AxL6EIhpY1SEkd6eK5Pre6DVgTSIEVOFqeMmeA7IXqakBcZQRQyMDmOU8YPQ7L0CKMLTJYyHceUyhWCoEZ/MqLIMoxSSGkhhIdXqlFpzXHY2aY32Ma1Q9JJQp4VZHmCoEzgOqByDrd3ueXY+MEparWIpeUWhxu3QBgeOrPI/Fwd8WD5nxHqfeaO8f7RMb+O+XXMr7+6/HrfZH7gP27KEvyIUeLBWOnsPyUa33Xw2026vQGH3SFSllheanL+wjk2ruccTofobEJ/5w5ZLrhshVx49CInn3kILXKkUCRJxunTZ1ksC2wzBaURUpDnBYPUJlEeV2/e5olTbYTROELQKNssLdYYGZePPneBtbLBRs9OQFJiVEYjsgkcC52kZJZGWoZREpNpjcoVxjgYy2WQGZJEUw9tar7BM2qGydka6gcnK40lJQrJqLC4252ilUG2S0jAk+rByQuQegYPJBiNRKOMJBcuB6lhqxdzarnKI+tVysHMAyPOYTjOidOUXFocDFPGgwwviFBegDIapTSu61HkGaoARwqkUAhHgVRMB0OYZpRcn1E8RuRj1tZXWFpbIhE+0ywn1zmlkk8jsBG6xubGDlboEwYl3Dhl1O0yPogxCJJcIZXCDUNMnKJUgZACrTXdXp9JmuKX6wRRBawAr1TGjUrg2ViWTWdnj3iUEFkJYaDwnFl/QZ6nlEsBB5tj+p0uWbzCYr3MqBpSqZTJVJ2nn1rHcx2MMbMT3YM1Bz/udPGPw/n0eOz9p0vH/Drm1zG//nyv8ef5+++r4OdH+pM+qh/9TOsfpfHq9TpeENE5GrDadPjA42eo+4YXJzGjwx6eG+H5EcJ2EJaNkZIkTRgPYqR03hkJFQiUksSZ4PpOzMbBkOvX7/LGi1/n1P/+7zLKLdJcoDLFyYUGncEEj4JauUwmC1ASJQRxkeO5HrZU5FKAZaN1RudwQLu9SKoUhbAZJAn9GAb9lKWqxYW1iMgySCyEJbB5cJIyBUprUuOwNdS8cb9HnmYU2uJUe3YzekLhSoMUs+0ts+vdwmAzyiVbI8UgLVisB1Q8SSQLLMeim7jsdGMc26YUlemNEmzbpoNFuVJHjabEqsCSGtv2EEZT6AKjDEJpwiAgikLGoxHjfh8hCkrNiIfPn+TcudMoL+DaRo9+v0+lHCDLNq6UBL6F5QpKfoTj+DNAWpI0TnHcgPrcPEG9jdGaUbdLYgnCUkgYlvDCkDDL8YKAPM2wbI+w2UR6AmkpFucb9De22T/Yxy5JGuUyJd8h8B2UzvF8H60U0+4hJh5Q8So0qz7nHzrNwd2MCw+fn11tggcAeXCcP9ax/sw65tcxv4759ZPWX0rw85M4Zb6b1xRCvPPBGjSRZxEuVPG9ARQtKp6gezRiszzAjRq0Vs9il1tguUwmGW4guX17g4OJYBRr/LPz+GWLSa7YG8EffvMaG1df5eYrX0ckA+5s/CKv3Z3QXlulXQtZbDX5uUqJdjPEdgUqg6woGOaCQks8G3JdkBSQK4OUHrudfYJqj0yGbHeO2NzrkBqHyTihGRiMOct8PWI8npIWikbVZqkREtkOObAzVnzjlTu8eXOfUsknDEIC18KxHIQLlgAjLJACoWdNl7G22BnE9GNDq+bTDCShbVCFIDUQOoK6bxHImHbJZ6kUMN8MuOba3A4cZFiiFDgk05i80ETlEkVeYHkl7CCksbTA0socg16Hdt2h2aiwsNjizNoSfmgzUhobTTaJccsBzdAjcgQTXVCtlMGNiOOcNCtQSmO5LpVonvb6OnapjsoKhOuyEKziOjZaa8bjMVVLEpWrTKYp0rFpzrc4fXKJZsXBUzmvfaWLIwxCQJJMscTMDC3LCxAWjfYCo36XeNwjcFdYni9T8tdgdJe11UWMUe9cZ+/HKYm/6jrm1zG/jvn13tf7NPPzn9c7KTPDbAGhgPlGDc/zwEjOnT9Jdc1BOSXOnr+EsH3i6QSlCqT08V2PnVubjCcJj63VoeIyLTSdUcbG7Q3uvf590s41LNfnDz7/R7x5Y5cTZ87z+LOP8Isff4Zzc1UcWzBSMI4F3UlBpsGxJTKPkcUU12SUfZdOPKbTTVAbh8TaZf8oJU4SGnMBqhB4UcTuQHH9/ibXr9+ltTDPpYtL2J5H07NJEVy+d8TV29uYVLJ4so7rWHT7fZaqLUDMauqA1gaJphCC3dGUiQalDJ4lECpDGUGmJdPCkBQKpQ21yKfqW8RpTigMiy2Xi4+ssdOqogtNMk3pdQcIy8ZxPSbjMX69RK1d4dzJRerRKqPplKQo8HwXy3fBZLhoQkvRqAQsNUusNSMsNPE0wNgu3WlBgcErRehCYQUhtbkW7fU1rLDMZDCi0gip1cuARbc3wKtV8V17NuLq+aS6oPX/Y+/PviW9zvtM8NnDN8YcZz55Ts6JBBIzQRKcRMmkaFmSXXZ1Valvqlf3n9Q3tVZ3X/miupfbdldX2ZIsS6ZEWRZFEgQJYkoAOWeeOU7MEd+8966LSJAsWSABMEFiiN8FFvKc+GL4zt5P7P2++/293TpXtts0fMfkdMh42KO0HjqsEcQenudjjOX48JiikvhRAzsYUuYVUkiasc/x/gEXtrs04gAhzM+PtF/veOZXDyF/2OdY6tenJb+W/Fry6x++/v0+x2d28fPzcg+zxg5Bq6F44spZxmnFyzdPUFHMpe2YRmuFXt/n9HTARC8m+cbGKlEcMZsMYHWDeam5vX+CJwXpfIx1Jc543Htwn2o64eZLf0d//zaPb9S5vPoCufXoJYIf3+xxdNAjyUs8rWhEklZNc2WrQVsrDFBYxWl/wmCaMxzmrHVqPH95A6UF1vr8+NWb3L23x9raGqvra7TqdQLPwwDjWcZ8POaJs+tsdVfY3IyZT0d0ooBmKAi1QAmBxYFx5HiME8O/+v/+OfdOZjz7+a/QqJ8nbCoqJzgZl8xyQ68/QYYRm6s1elOLdCXduk9c1wRqg9udGtPMUo9ier0xN+/tE8Q12noV7UtWG5qdjTqeMxjrMehPMR4MphOunWtR8wVKbfJ21Oex3Q5bTckoqdjoxLSNJpoVOOcYTxKCyCeoNYlaXfxmDZSk2apRCyPWVloMxynzPKDRrjOfDDDW4ERFo16n24xpBoK6B7pVZ3f3HO/cOqQSAj+O8ZTAU3B6fEhZSJT0sUWBwuEpD1cZiiThuUvn8OTPziz8TOKnI22ppR61lvxa8mvJrw+uj+Xi51HsOj9QGPmnZk6ANTRDxW+/+BSrqycMRgk7XR+/rglEk+l4TlY4KiHY3t1mdaVNLc7JjeAHb97ltZsDZrMxpiyQ1lKv1/nmH/wzStFgeHzCKz/4Af/xT/8zZy9dJOx0eef2gD/5d9/mwRuv4Pk+Yb3G+tY6Tzz1OOc3GkglCOOAylSkc8t8Nmel3uC5K2e4draJMY7vfPctlLM89cRVokCw3VVc6np0QodQoLTPbz97kcBTBFoQ+OBsA08IQmnxhME6QV5JZkZw6/4p/+bf/Cnf/rP/QGEs08kcT32Dxy5t8PbNA+7cP+TW9TfYu32DIG7z1W/9AV944Ske242oaUnNgm5IGhea3B0WlCWEu22a3YhcQF5WiLyiW9OcTIZIW9GptXh8e4VGI2Sel4QO6s5yoRMQi1V22h51ZdBIAqeRQUSjFhEGHoNJQjo3jE7HxI0GQegjpCAOA9Y7PnEoKLKUej2gVq8T+Yu0QZYZrIFa4BN4AqVBeoqysnheiHHghyHzJCEEBkcHUCkq47D5DE9cIPAE83lOqxZybnsNZ6uHrHgXIJ/ckPEy+vPhtOTXkl9Lfv3m9cvm0Mdy8fPrlwPMTw/+IQQ+FRe325TJmMgHnMFTEDdqaKWYTSVnz6xS14pG6FE4iRKKzfUONe8a6ekdBjcd3bUO/+L3vsTq2iZ7o4KgVue/fPsv+Zf/9jvoxiYP3n6H+z/8E0x+CtLHUz7jox3iesRT5zuIbpdGFNBtx9w/meIpuHK+xbNPbOIJy2iecPH8Gs8327TrIa7MqMeKtaaiKCpMKalrSaNpUcKgkEjpFlbxKACstFRWMakEP3prj3/5//yXvPrSf8Fkp0gVcOuVl5jPDHg+2XzM6f13yId7yLDO1W/9Fqqzzbd/8DZ//hdHfP35i3zjy1dZiwWNEMpSM0wq1lo+lVFM8xJTCNZbbXwpOBhO0DKiKSVbq00cUBgfJaGwEucc3UgSCYe0llBIrK8QvqDEMsscgpB5CKs7LdqtiM12DA5iLVmr+xgqAu0T6ZJGqFkJOmgJ08JyMlxUWBgDBRZjCvLZCFPmyHgNo9vc62d0TIhNE2a9QzLnsXVmh067jbACT2l2VyMa0bugEH9vbH0y9fFq/7DUe2vJryW/lvz6+3r3bNx7abn4gZ/+rcXP/wNohIooUCSFpagK8koQhJrY1zR3tulsrmDmc2Q1I/YCvvz0efpJxa2DOlX5BxxsnGdnpeLyVofIFxjr88RTj7P34IC3vv9DhBXMkwllOkfZAkeGdZZJVXF6/zaN4AtoLYkCSaMeEs8MlRasrzToNDziUOCJgLNrDQKlCDUIo1ESNBahHM45Amkfli3ahZWa0yAtOIezUFaSWeV46fV7/D/+X/8zb7/0N8hyiLApDsNscMDJrZAsnVEWQ/KipN5c4Xf+6T/la3/4j0ldzH0t+C9vvMbNd25zcDLgD77xOdrtkMiTlD50PUscKUxdL6z8pUFKQV3XKfOCZuATKEGJwzhL4RTjuWGQVExnGYF0xJ7D1yGepwiNI9SClWaElBWVyXjm2gUacYhWkvksoRnGaCxZDrPJjFYUY1PDOJ1x8eIGdu6oThNG05T+OKLd0Eih0bjFzqvZZl4KzDAhryxlOmVyfBcR1sk7NaJ6jdJUKFHR7cRo9fcG1FJL/Tq05NeSX0t+fWAtFz+/QBJDvV7jJC3IHNTqLXyvIvAkK0FM5Fls7DGeGJSGWFucM9xXjrDZZnXnAufWC7QUCwMzAVu7G/yj3/8n/Nv/6f/O6Z2fYFWJEw6ERDx8nFCW87vrbG+vgGdRxuIpQasZU6aOTiNE24LAWrQHnqcXPhzOIYVBKYV1Aq3kw88hQHgYsTDPl9ahrSN3jru9gu/98CZ/9Zd/yZuvv8zk4D66muFcjkGBkwg7Y9Z/G5unOOWxefEpfusf/zP+yR98he5Kjet7JTtnVvnW732Lvf1D7g3mvHz9iGuXNsBXNGNJI5JoJyjKh95tToIRyMJSD0CHgknmSCooUNy5P+Jvvvsjjk+HpGmOq1JMPqZWb1KvRXz1S1/kzM4O49RxOEw5HU1YW+sgAompQOIzGM6Ze5rD4QTl+4RhyOHBmCRN2bGCm7cfcDpKaJ5Z42SUklY+oXTU1rc4v74oOZ1MxnRqDYJQYospZn6CK8YMez55lZNXJTVZ0q2HCxgj+TQETJZRn0++lvxa8mvJr/fWx2bx835z3B8mn/6hHVcdRGHE+KRPvb1OPZQMZw4rBO1WhBOGaVWQGAnWR+eCw0HG7fvH3Pjx9+ndfovGs2eYl/8YJcFTjsubLTzrcemZZzk9uoOd99FhhO83EX6Mw9Lsdnj86mO0Qw9flFglOL+zxeTGHkEgCKSBKseWBqE9nC1RSmJMhRUSh0Q//NwW8bBBoaVSi87G88zR8BW5cLxzMueNvSH390+YnjyAvI8VDiE9pHFgK4yYUXiWRneVi4+/wNlrn+PCE4/TatagMESUbK3HPLO7RfX8JtZCJ4KWL9AajHL4GKxVKOlwQO4Ew1HOSW/I7sVVysSyd3/K3/3dKyRFwv6DPV5/+WXy2RhfKbQyJPMBzi1KNn/wZ3/M1u4FrAopnCQ3lkazRbPVpd5eZXNrh73jY0pj2bl6hU474PaNe9y+cRfPC6hHMT/6wcs8+eyT7O6sUpUVw1mGKTJWzp1HejU832PYO8QThspUWFtg8gmi0ki7vRgk1hJoCLVECMen7ZjMchH0/rTk15JfS359/PSL+PWxWfy8l36Thy4dglocUtND1lshvhJIBCfHp1zubGOBvHQkpeS1n9wlCDrcv/+A7/75v2fv+ktoCfprz/LSnQmtpmBnLWCtJrArAU9+4fNMCji5cwepA+rdNRqdFbSCrTNdLj7xBLGv8JzB+ZL1Th3PztnaXkHZHFMWGA+kEIts/8MmdAhJWTqEUKTGkZSGn7x6k7/5ux8R1OtsbK9z//CUrdVNSitobK7zW9/6MkJHvOT53H/lPyLLHOXUoquQlOjmKtee/QL/3X/7z3nm6SsI4eNpQeQJktJxdiWkGwvqvkFJqJxACIkwBuUkOIFEUjmHUI7KCkaTnL/47sucjgxf9eq88oPv81d/+hfs3X2HLO+jbIkqc4QpMX6E1T6mmKNsiWcs471DxgevgVBIIUFpDpWH9drU2zu0ultIHeKUJtIed8cTRocHDE8P8AOP03u3CFohT1/ZolVTDCclsyQh9j02tjdAepw+uM/s4Cby3ArdzbPEKytYLL4z+FISaI0nIfYUvgSBXOyCl1rqoZb8WvJrya+Ppz72i5/fpIRwRJ5krRnS8CSVECigmCcAZGmFdJZ2FLCx0uXm/RGvvXad/bevE/o+X/ztb9HZvcZf/eAOzigu7DT54pNb7K7V+Z3PX+Hc7hZv37jP4cmUztoK62stosBRVCVWe1RCocRigIYaLmyvsr2xgioXTfMiGyCsQwiLZeFxYRyUFialYX+Q8t3vv8af/bv/wPHeXVw5Q7qKUgjiWhtd6/LNf/4viOs1VnfOcPm5r5P0j8n6BwitOXPlSeJml+3dXX7361/m2ctrtGND6C+AYHAUkUJJSaBAWoVzlgpBbiFzC9gGAjwhEMJRODidGP7dn/yQP/uLv+Ta8y/yr/7nP+Hl//y/kQ/2EHaKL0qEdUjncFJQuRJhBBaJjlfQVJTTPtJlCPfwDEBlAYELHC6tkfRyPK0xVcnNpMdsNsGmCaaYkyvLfLDPH/xf/m+0Ok1O+lMOTiaUpaHUBXmREEYho6M77L32fZ54fAf/ygVaK+s4qXEPreK1MGhbUAsDpHA43M/6Mi211G9YS34t+bXk13vrAy9+PsqdzAd97o+8pFRYpHDEoU9eGSoBZVkRKElRCeazBFdkxKHHhc0Wre4Kzlbkp4fMZyNWzz1Bmjv6R30Gg4zrr2cI8wwXfvcaT62FXNmIeOFql8G0wlSOZixo1DSjxDI8HZNmFTqUOCEZTYa0m3XaNR+bL95XWpb4CDwEEkVlLGle4EUBrUZIGAd44nk8FfPjV15lNuhxsnefPB1hqpQsmTGdpwSRz+WLdca9AduXP4/c6XP1mWuceexJPM8j7R3y5KVVOnVHJAVSOFACX0DkJFIUSAROaConMQu7DZACsGgh0MIt7l8luHuScPPBKek8Ix0Puf3OW7RabeqbK+zv3yObHKOxLALMJWAQNkeUhp3HHmc8GpLMcqzNUZ7GC+vk8xmeH9LoXMAJRZEMSbMxkpJp/xbW5WihwAkslsDzsHnJt//8uxz0R6ztXmCl0yUtMtI0I89Seod7FJMe+++8yeq156m1uyilwFqsNXhK4gtLoOXCY2QxaH7lMbnUR6clv5b8WvJryS/4GEV+Pn6eIg7nLOCRVY5hWTJ3c04mY+pxyL3eBJ3nhFoQKMk8SRBBg7W1BiLwETNDKwICn7KskB5EQZs3bp3w3e0WL1zepFvz2IolW3UfKcGzAuGgpQQ16xOGGikMqbHcvHvE41e2ibTEOZ+8LEjyAotEAk54FAZ8T9CIQKsKzxk2rjQIWp/Dtte4e2ufaL3HZHhMHAX4tYgrly6yUdMUOGoNj889f5UvPLHD7rlNrDMkheW+6bPeWByIVEICAmMclZQY5/ClwmGpMGROkRmBFIuKDdwi75oimRcwzhwVis3dDaL4q6y0Wzz7zCW2z27j1ZvcuX2f13/wN7z18o+YnhziyhGmmlCZHCkVd268xe61L/DNL/8u3/8v/4Wo3iTLMoQ6RYQ1wuYu45N3sLMDTJUtECQcTqrFThSHEh7ZeMx//Nf/htb2RZ7/rd8iatcIA9AqYDo13L9xm/kkQSrB4d27rNw/JqjVka5AOU0QhNRrMXVPEirJz3pvL/VZ1JJfS34t+fXJ0sdm8fNxlEDh3OKQ3WBWca/X48adO1zY2WR1bZ1O3cNlM+IwZm+S893vvcxrP3yJMjvlf/wffo/LVy7x6s0jpBKsn90iLxwn0xH/v++8yvHUcH6txoXNFiutAC1ASYc2JRGO1bq/sJgylkDA89fO0WmF+KYgd4LKafLUILGLHZ60VGVJO/bRWHwcCofDUPcMrZrl8acv87YfUV9rE0c+zzxxlq8+t03sCY5GBV97/iLnmhcXeX0DUnrMi4pLq1cItUDIh3l0BwWSWeEYTDPONAJC32NaVhxNM3Kj6dY1wgqm1eI9zjLHYJKx0q7R8OG5x7Y4f+5ztBoe9RgqJNMUdleu8aUXHuPVn/w2b77yKreuv8yN119CpGOsNXQvPcHX/+j/ynBa8OLaVXwv5N7NO7g8pcpnzI9uUc2PkCZFCEGlApRzKAeIRTdmK6G+ss7qhatc/dyzPPfcVTIHkyRb9EpSkgdvvM7GagNsyXTQ4+jefdbbEovGyoBud43YV8SBxFMPy3AdgOQfKpf4dX45/qJDfh+/L+mlPiot+bXk15Jf761f6+Lno6x0+FVuynteK8A6g+d73Li1z9t3p/QGfdY6qwRK4imwEgIh6DYiZv0x99+5xT/7p5/nhecuLiabMPhBBEqTVTNWVlq0mjX2TufMCsGN/QnnNju06j4XVmPWQwikI1IOYxaVGZ6WbK41qcoCpA++IMkSZpkjavvkQlKkJdpZtOc93CUIhPQAyWpN8PtfucCDQYEoJ5zf2CKqNWlHip0aaGcwocIKxUZc4IkSpzycs7QCixIKtbgdi0OSSCZGsD817J9WSOWx6UmEVGgfbu/NGWQRCkt/lPHgYEBhBKudOp12HS0NLzy9Q6A1Qjg0UFSLz+spy0rHo/aFx3jh6ccYjL/Fv/p//yt++Ld/iykLdp/+MrXVDUQt57nPPY11gt0rV3j71df4yXf+HdO9l8AOqJxFoZC2whmLdA6hBKX0aJ65zJd+/4+wtS0ef/YCZ3abzHOLGkqm84Rm7EE64ejOEVQZVeUxHvTZbG8ihIdTdc5dvEoUasJA4oQBZxHofxAcS306tOTXkl9Lfn169JmJ/HwYuCzyoA5nHbffuU3/BApTMOiNGY0neG2NVgonStq1gKeevcLh0QFPPf95vFqTk36fwlhMljE4PeXMhTP8s2+9wEasyYXgL1+6xY+v3+N6s0a7XePFp3b5wqUObV2iWBh7eUpixcK1NRceg9QifI/7/RGl8SkSSxR5mLxgvRagpEBKixOWEg1W0NQCz8FcGf7xFy+w3dLsjwwahy8NCIFWBl8KPKB0EovAWkvkgbKLkGhZWTKnGJeO/anl+28esN+bMr64ytMXVoiVIYp8Lm43ME4Q+IJaHFAaRbdVo+0bvDJF12Jyq0kSi1AC7QmSEiZzQ+xLFI66dtDUeHGX3/tv/3vOXvsSlbXgh+ysd2jXFKFyDOc5w8jQGx5jkh6yGi3M1tAPDdEqyoeH+ZTzwG/w1Iv/iM9/5avEjSZRrElzS388IcssoQ4wQYAVFeW0R1nMUVFEq1VnfWUFKT0aq9ucu/IESoDv60XAWIBDPuphu9RSwJJfS34t+fWo9ZlY/HyoHdvD66RzBEoyPj1lclrRXu8ilWSW5mx1IpS0CFdR8xQXzq6xef48xxMY/uQew/EAQ41R74j7t96mFVfsrnyJM7HHuHCY6ZRkkqJ0AL7hxl6fC9tNZChoehotDGCQGJwNmBSKm70JWVHwt997g/baJp1WTDOKGB7t87tffhapNVpUOAzWLZodSgRaKNqRJgoVgYOqsEgNQipmRUVeFTRqkhLJtLRk6Yw48vCtWDROlJq0cvQyOJrDzf0Z19854GD/lPHplKTwaTUkrbqhEfpEvqQyMM8scajYbEpaviOzEbf7GafjDJRPXFPUa5q8NGRJhRABRSFQYjH5Q2m5emmdjfVVDI7RrKBdh2YAnhQIAvp16KxuMlrdJT29iyxAUOCkxdpFOF5KiZUha2cf4+nPf5m1tTaRL7BWMC8t1iokElsZjAHpe2BTnCnI0ym2nLG50SFqtDn7+FO0VrvEocZTGsfCiM391GP3vx5vy1TUUh9WS34t+bXk16PXZ2Lx86HlFjco9jy0K8lmPdaeOsv6+TOM8ooyyahFEqU0xoBwDqEkf/LHf442BTvnz9LdCEmrgq1zZ3j6+ec4GZVURcU4k/ROJ4hyUV7oYYh8hRUwmM4JWjWkp5DOUgmf0Vzx9l6fN+/0uH/jJj/6u7+m1W5Ti2Iwjs2dLZ579glqE8lKHOJLjUNinUNIA1oRBooQQ+k0uROUpWFSedw4KXlwNOXKpqDT8PjhKzd4/ukL1HVIYS1WKJLckpSSvZllb1Rye3/I0YMDxgcnlLMZeCFeLWR9tclGu0YcaaQSCOdYrWlqARinuH2S8MO3jxlOClCaWjOk0YiRUuHJxSRTTrJS95DW4unFzq3WkiAcK7GHcRbP1xgLDks9FHzlqy9wdqPB9/7Mp/fWj8im96jcDK00Conx6nTPPcOTX/1dts6eI/QFoS+pjMUiacYRpWcpywxReHgKMrk4iyDKGefW62yuNwhrbZqrW1gqGrUA6R6iQzzcZf+Gh+xSS/1US34t+bXk13vqAy1+nHMf2SrvUeTGH3V+XQJGODwPYm+RP3dCcO/BIZNmjd2mh3MSLwzwpWAlEnz52Qvc+NGPOLx7l263yZkzG3zxS8/Q7ba5cvUqf/vya7z+yuusrO/yYO+EjbUOX/zceS7trtCMFB1PEHoxWgiwDoNiVCpevjPkjVv7vPqD73PnjdfIp0OS4wOUlGzv7vLCs9/EWMPxYI4koBEEKOGwOMoKYgmxdEgpGBWGQsDpKOc0cfzgx3fpDRNmmSL0cqLWJsNckhyP2GrXmTvBySRH+jEHw5QfvvqA/tGI+XCMKxKSqePOm9fx45jZaofpxiqNbouo5rNW17RWPayA/UHOy28ecutWn9FwjHEV69vrtDfWqBzUIo1wJc6FKF9T0xLtLM6Bs6AltGqacem4uT/GGEmnHRJoQ6OuuXjtMlH4R7z8nXVuvvId7PAOSI3X3mXn4jWe+8pv89jTTxFGIQpHICHw5KKnjVTMpaWqDKGvCbVjmE9xSKSFiIpa7CFkRe/wHr57jLovHu6SLDjxcwZhH7+8+Sd1d/YoteTXkl9Lfi359a4+NZGfjwRqDowArQXtZoxUHsPTMdPTDHnxLMO0Q5UWdBo1mrHmTNPDyC5nL17g4N4t2q0aLz57CaF9SgOtSLKzvcU7bx/w+ms32d7s8s3ffppnHlvDZjkbbY+mB76Q4ByVdSRG8cbtPn/13Ve58dpP2H/zhxhjOXfpGgf7D4gCyT//F7/Pi597jCjUaAGhrzFYlHDkpWWUlHhK4ynJvBI8GBoenKTcut9j1B8x6g1BSN68+YA4gqu7a7x145irZzcwwqOqFNLXJJXDWIHvxySTPabDPsqUaM8jHQ45ffCA3v2Q5MoVWhubrG502OlsUjmPW4dzvv+TO/z41TtQakzhyJI5c8/D8zysr1HWZygq4tijPi9pdj2EhLRyJIUjSXOakceodPzdK3doNzs829wlM5BmJc5WnL1yHi/6Q0aTAUc3Hecfe5wLT7/IY48/wZkzG4SRxjpDVS06QfsalAJpDVWRY4xDK496PcYWCSBx0mc6moITCFJENqHhS0Jv4WEiHvbT/tl/P5h+PqS8XKR8NrXk15JfS379evWpWfx8JBISwSIfurrWRYdHDE/7JIVkXwiyxzaohY7KGUo0FslkntDaWuOpz79IOktoeI5WK8AJn0ZTU6tvMU+fplkL+OoLj/H845vYIqfb8GhGEt8ZhDWUKObO4/qDAd/53lu89aOXOXr7ZZTNWDv3JDtPfI7Tec6Xv/A4L37hWVZiSeQvbNnzsgKtyK2jkoqj0YzCOjZWa7zzYMYP3hny4HDI6dEJ+XSEBuqdJs6UbHZWONMO2Nx6jGlhudUvmc5z8D3SsqSowNmK094Rk+GAUBhqXkhcq+Mpj8JUJNMEv5aQNkImecmdo4q7t/d49ZWb9PaPqMc1pPBI51N6Bwl4guZKF+EpqrJinuaYusLTi4LX0jhO5zmZVRyflBweDXn7rX0ev9agPzeUJfSHCVJCXUjWz2/zxW/+HjfWNrj23OdZ317n/HaXRqgJPIkTHsZCXlmMgKoC4SDQHi5U5Kaks9IFYxACpOexf9SnN5jjDIT+4gCkVnLhpSJAfKa8UZf6RGjJryW/lvx6T30sS91/2eM+6tDxuytZhwPn8CSsb3TwAsW4f0qZW3rOcOfOOo//1rMgFpboWZIRBj5ndzbpPzhidP8B2ma0ax1QIWDohIJvfekc/+iZLVZbAUqBNSFNn0V+HEUmNPdPM+6fTPib7/2Yl//uh5zcfA1dTHFRjbNPPE19dZ2nn32K3/vWl+k2fGIPBJbRrGRuNNozeL4mdZJhLnlwd8h6pvney7d57Sc3KAuHsAZpS+JmA4SjWROcXY/Y3OwymJe8dP2A+4djgqjG1sYqZZ4Rtzo0Wy22d7bJegekg1O01EipqTViakpihcRWJXkypzcY0TeO+0d9RoMB+fgEO1N4UZ0iN5SlgiNJrRFjSgXSJytKlK8X0VfjEBY8z2eSG8YGkkrQ7qxQGse9gx5aKybTDAQktiBIS/zWKpef/QqV71FvNYhjja/F4n4jEIrFOQcWxmoSiRACT0MxH9Ns139W9Skco8mMw6MhDkmzEbHWaeApufDGEGZhhuYE7lNSKvru/Pgk7eQ+ai35teTXkl+fDL2fefSJi/x8GHB8WNt5JxZhQCEqOt0aQahwpsIVOfnwlGQ0IvYE7Zq/aALoQyVApWNuvn0dNz4mL1JyA7l1GKEIlCOWhrCuFiHR0iCtQ4SKqoBxXnEwM7zzYMK3/+Kvef2lvyU9uo+q5lgp8NvrbJ0/z872BptPrnHx7BqeJ0iNY17A3X7OjYMjVpuaszvb9Cc5P3zlNm+/fYfV9U3u3d/DpXOisEYQBjgLUgrqkcflcxtsbqzw/Z/c4+behL2TMcPJnFa3RZFXDE+HNNpDVrY3WdvaJO1f5EGWkxQZcVsjfB8/DnFSUpqKWhyTzytm4wlFWhJ5mrmtKLI5zsHK+hallcyzgrKoKIqKsgIhPYTSpIXFA8JA4BcWLaAoDGmaUQsjRsMhFQW+H1BVFqkUxaigKmZkkxRPCuqBQEuwTpAaizWL4K4vBIFUeGKRGpDCEfoKVxiiwCcMfRwGnMSUBWWeYUqHlCHrqx3WOnWwBsTCHXUh8RAmH2i4LfUZ0pJfS34t+fXx0Cdu8fNe+ij65AghsM7hjKEWBXjSQ6LxfAtUgMBXHsItqgICZahZw7Xz21y+fJ7psUfmPI7ncL8/ZlZaLm61ONdReMJRGsc4KWkEHoUVCKGQWmK1pD9KuffWWyT77+DZHK09MhWxvXuBx85tcvXsGptNRS1cHKa7d9BjVmnu9Oa8ffeA4LFdxqnjh6/c4q//6gdMp3OUDGjVYlIlcEIS1EJ8TyOFII4Dqgq+/d23ufdgzNFhn9lohJQKmcyZH/dIpjmDWh/la+qtFl7cYGXzDEVRUNmKsiqoRS2CKKIWR+RpSv+wRzqbY0oDThFGDbAOV5Vksxn11U1qcR1jHXlWkKYFWnoUlWSQAMbQbGjAMR8n9Pb6PLj5AFsahJYkDkzkFlUW2pKXBVVZ4kpL3IzodpoIrUkMzCYpRVWgBKw1a4SRwlkorMPYhfW9Q+D5PkI+DAlbgaCkymdURYH2IjqdNu1miBQOuyiWWHzJOPfTctGPm34aDVhGcj6WWvJrya8lv95bHwW/Hsni56NyPv35x7zfQ1Uf9Hl/kezDkeGwtBpNGnGLfpBTyBTlaU6nBf1pAU7QbMQopdHOoUXFynqHeqToZ5Ybbx/xzn7CNC+4fbfG77xwkTNdHyktQeATKAkWpANPwmg85e6DA6ajCaIssAqM9Gm01/idr32Zp89vsFIT1H2LJxxJVRF6irBWx4/rxIFmZ3uD8TTj7XduEdVr7Fw8xxNPXmBzc4Xe6QxXLUodi7KkP5zixyGv3zmgf5oy7I1JJwNcniH8mMlwvJgYlcSVBf3jI5TnkxYFyg+oBx7KD1FRhPY19UaNLJmTzMaLUtiqxFSOJCuZ5gXWFFRZSpLNyYHLzz5Hs9VgMh4jbImWgvEsJ9GaoigptGSSGm7fPuKNl99gOprRbjXwfM28KCizFN/3AUVWlAS+xjmLFwQI6TOYZIxmGaPRECkF7UZEtyWphMNZQWkhLSq00jgnSPMSL4hALFCgnKXKpmgl8MMG62trhL5CCMu79RJLfXK15NeSX0t+ffb0sYv8/LLQ76PIl3+ANwNCIZyjEQe01joEM40qCvxQ4vyYvfGctW6LUEmckxSVRQnLbz9zlnme058UXL9xyHQqGE+nzE59wsDjiSubrLZC1mqSFc8QCCik4nhsePNen9E8xZQVyAjhSfzWKl/6ra/yO195lm4N4sChpMM5SegH7G4EKCXIK8PZ9gZG+mRpwYXLu+xcvsDFc5s8f2WNbghHwzqF0+S5JUlTzmytMEhK9o9PGZ2OKPMC5wzCV+RVjrAOX3k4D0qT4WuPYp7gygxXJBTWYfOCRuTjhCPL5xRVQVZBLQipCoeRBc1uC08L+r0DtImoCoNzjizN6K6vETYNtUZEt+EjhKNwcDzJOBknjE/H3Llxj2Q8gSKjmBpKqUD7mEYD6wdUlcFJiSZEaUWRJAz7Dul5VFWFdRW1egTKw9qFA+ziOCjkRnDnuE+VF9S0ABXhZA1MhnJg5gOMMYSdFc5ud9FS4NzDhoBOfsYcMpZ6Ly35teTXkl+fDH3ki59/aEL/IrfI93P9r/K49/26ixNgWCxSgNKKJ55+ElGfsX//AWWR0F7bpJcYksKhwgqBRVlohz6N9Tq9meL1799ldDJmeHzC0d4+Oo4x0wFUz3Pl6jmCoEZkBVklGWeWB6OSee7Q2kOEMf7aGTqba1y+eJ7f//1vstKpoUyOFBJnDRa18HIQAmsNnpCoQKOk4smtFmvNp5ChJvAVnQBqsiL2I2aF5OB4Qr0ZMCstk6wkCGs40UdIjRAB82SKVppIKqxzNNe6rO+ss3Jmg6OTIZWxGKPRgUJrhZSCMAqJY4+11e7CWGxaYKsJdR88rfDDGn6jga8VRVEhgwAVBMzShCDwqNdrICXD8ZTBNGc4Thn0RySDMSYv6LSbzIcl2aSPqRxe3KQqKjLPQ/seKgjIMqjVahRZgdASbRd/T+17BGEIQvzceKlALsLFr7z0Bm/+8GUev7BDJzIo5YGtFi6pszFKGFqdJpvrnYdfLIsKicX/yk9Ervz9RiDefdwHmaufRi35teTXkl8fH31Qfv0ifewiPx+FPixYHAt44BxWeMRhjfloj9HxIUpJvCDg1bduc7ZxhZ3GKtpVSOeoB47xvEDgSMYTpid7HLzzE7LpAOMs1WwfpRRJrrh/NyRQBotjmqesr63QbrU4DUfUVzd47MoL7Oxu8cS5dc7tbnJ43Ecp2OzUCdSiUV9lF3/oxRRwICyRv6h+WK9prFJklUEKkEKihcXM56xFilYrZlJY7h9PMBXY0mGMpdFu0Ow2yHNDOp7QWenwzBeeYWNnldPJkFYRwYULnOz3qVyO70u66ytsbK2x0m2gtUdvmFBWc1TpiLsxoe8h/IiIdZRUOCHwPMHKahPf11RFTpZX9Po5J8cjjnoDwnoThMILI5SB0XjEeHBMORniaR9PK1APJ66SYC2ucotdGSVeHFNZg/YkYRyiAx8nJBZJacATErO4Zaw3a3zv6C4/3HuV55+6hO9pCiPASawt8UTF9lqb7a2NRzc4l1rql2jJryW/lvx69PrAi59HuUN5v9UNH3ryP4L8+aJFniBJSl7/yRvcvn6DdDImiAJiZVg5v8O0sMxlgFdWOGcpqShR9IcjZpMBB3deIx3cwxRTrCsZ7accrF5kXtWoqhIwpEXC+cfOs7G9yeZKk/Fpg3Pnz/HlL73AWkuzu9bi+HTK37z0JleunGVro0OgISkXoWOHQSuJsBXOVlgpcUpgHeQGrDFozyfJLdPMUPM82k0PoSqkEoR64QnhaZ9rV3b48hcvE9QjXrtxwksvv8Plc5s8dmUb7Qm6nS1GnZTJhiVu1UmTOc3Y4/zZLZrdOrXYozSGIGqD8FChxm+GNGsRaElpHcoJ6nFAs+HTbcc4B6eDCcPhnPHdQ26+fYMgiumsbRHUG4x6feZZQZFllGlKkc1RoQNXojxJVAt5NwSs5GJnZI2lLAqUVIRxDe15lMZSGkmSV3hCoeXDw55S8MyzT1DO/oD/9Cf/f3q9AaayICROeVhn8GXFpXOb1OMA8XO7r09jdOTTWuq+5NeSX0t+fXb49Yv0G4n8fBAYfJTg+OUSD3ufCIajhIP9HsU8garAFJb+wT1+58mvQ5nzyjsPWIkV3ZrPaJJycjJh/7DH4GSP+WQfW01xtuThmp1QFZw9t8b61jaeclTJlFqnxmpds9pQrLUjwicusrtWp1NzFLbkx+/c5+5JwvlLGl9qyjJnnluKIqMR+3gKpJQgFCWC0ijmlWSSVbSChZNnf56TV5IV7fBEhRMCW1ZcPrtOrlsEkebLT+/ytWurGAlObDGuNButgJ2tOrY0GFOyu7ZCf25pd2NMnrPdiVlpBAgqolhROY9B4vCV5LjpkdqStXZIHECa5Wy0W9R8QSPWeFqQV46qDJnNc+69fZt8PqfTbtFsxWSAn8UUSUYY1wnjOiZPsMojqDeQgY+TEl97CK0RUmDLgrJ0IC3NsAXOUeQF0mqEEEyzisBT+NLSDjRYqFzAU196kUazy60fv8SD699H6BCBRtoCYUqefOw8vrfofvxphMZSv1xLfi35teTXJ18fS5PDj89zS8DiEKSFJa8WP5NaIpXm+OCU2WjMtcfPMu4PmaQ5ZVVQZRXGGNY6LXwhEQT4jU1MZTFVgUGxf+8W20+ccO5Lz7LdDViLBDIQ2KzA147N1QYrkc9GJ2I0GzPMC+4ejTg87DEe9JnO1kizggf9EWc21lDaw1MOiSOvYDIvGWclvUySFCVPnWtSpoa9UUlv/5AXLnZoNdqczizzHLpRwJlmhv/kFlfPtmkqi0GwVve4sLtKleeUxiGrgvWmRxiAQmCNj3I+mw2PpudoxB5SQGYcoqqINn3qDU1vNOFM28O0NFkesFYPqGlHoBxaCzIjwMUY66guneE0Vly+coHWeoOj8Qwv8GivdJFFDq4CpbHGEtQ7OKmRQiKVRMh3D/FZqqqASlJlOSYKKI3DKkVeWQSWwFesBvqhFwrUax7aq7P1tc/xxIVVbrz876kqMC5AmpQyLzi7uwmYh2Pjsw2Pz5qW/Frya8mvT48+9OLnUe9+3m+o+FEdIHxfB6eEwLqF4+dgkjCdJVhborUizwryAu7tn9JuxZgko16rM0mHbDZj2jVFlRc06212z7+AV6tTGJBKI6noDfrcunGDZ567xrNnLrBadzih8JSPEY61To0iDsnKnPHc8da9Q05OR3QaMd1mzMl4wiQ19OeW6b0eW+2Qy7srKCHIs4ogCFDWcbA35Hg4pe5reofHXL8/4MJaQKPdZJgWvH67R+hFXDm7zrWNGlY3qXkKJ6Fyi75AG82AwdhydJqw09U0axJfOionGCnBPK2YpZKmvwjDKmexAtqxR+TAOIG2IeuxACnJfGiFUPME3sO/QyAhi0Bt1NhcucRsukOzFdHPSqR0BL6HLQReHNNc38QPI5JZQhA1kFI9/Bs68jwDFr4ZVVVR5YIsUXhhgHhYTlpWhrwwpEVJVUgyawm0hycEpVnAbPvsJl4YkU0zrIgJajXiKKZZD9/X+Psk69OW6vqHtOTXkl9Lfn069X7n2COP/HwUZl0fhX6pBT0Lu3XhBJWQHB2PmPf2yUcDnF/HAYODPd54o8HN+z2untvki0/G+MKQ54aNhk9GyYUnr6DO+Dg/IqjXaLY7RJ7m9GTAg5MBw2nJZFawXg/QQOFgVllG0xlOBFy/cwjG0js+5oWnr9AKFdcu71IPJWFScuNoj5eu77FS93n26ll8Cc+eX+dsS+F5cG6jwTB3/KeXbkGecPXqBc62BfPMkpWWsxttVuox9RC0LzACshIGOcwLKCuoSYtohAxmBTMjmVeOWWW508u5czTnYP+ERtzg3HaDy9s1tto+8mG+Hgc1DV7NI/IE0kEtfNiQT1iMkxgLUsBWTbJaE6QGkrZmlBmYFXTrNYRRzIo5vvbIlE/U7iD8AO2HCATpPIOyIstGeL7CoFBeiBAa56AsC4QxuLwkdDHOE0xGFZEE6wvaNbEwJzOOtCgwyRzn1zEiRdW6rJzZpNvuUA/k/9EUdalPlZb8WvJrya/Phj7R1V4ftgz1/cBJ4HDOIgHnNIP+kCKdkc+HVEWGF9RIBgn7N+/S3T2HO3uGPMlYb8T4qsDaEitgdbPLTAuanQ3WNzq0WnXazYCi2uXP/+4mqhZiQk0lJePU8ertHjf3DlHCQznBzbdf56nLu3z12Uuc29mgVfNpBpKqNGSBorPaJAwi3njjDvduHrHaibi8/ds4V1FTcGE94jRxnBwcIYVhsxWw3Ymoa8tKPUQpg7/4tGAlVikmac7LdyaMUsWZTsDFzRrDFO4epjw4nnKr6eOc5PhwTD6d8cNv/0eMg/bGChcuXuD3vvVV1ldCTFUQRAFIQRBotARp37XcF5iHFluCxUD09MIkzRRQOUfdc5xdiRkkgv7pnKwEoTycVODAj2tEYURZVhTjKWU6Yzoe0Om2kZ6HVIuWx3GjhlKKvCjJy4wkTSnzmI2VFqPxHFHziKOAorTM8gohJAd7R+SlIKp12br6OO1ui0ariecpcIbPesh4qV9dS34t+bXk129Ov1K116N0I/2HHvthQscf9P39oscJuSgXLYqK8XhGVVU4Vy46JUsfsgqShNlpn5OTU9IzNeKViMj3mc2njNMMHWjWVnw2NjvUayGNukIpR2+cc/bSFjrwGSclNyvBjXt9XnvnHv2TAbI0lGmCFCndZsSVnRVWGhKlDFWR42mftVjzuYsbnPQSbFow7o9YabexZUWaVdQ8TYQjdIZyNuPcasz5lYhOqIhFiacMCIPFo8AH41A4VOSxfzpCEtI512Q4K3jz5pi33riLUZJRu05ZVJSTMXdf/S77r/8lpkh5EIQ8eOcaqysbPPHsZTp1DyUdFodc3DQc9qfpZukcOKjcwqXUWUE/qRgnBqklSgkCT4EpmQzHTMcZLi+QnoeSHr7WaKkoTYLQkqLMqYqC/vEpK5s7lJWhUYuoN2J830MIRVYYTvoDqqJASU1lHEXlSApLlueUBqLQIwhjpFdnZaXL5vmL+IFEBYsqCR7uCJf8+ORpya8lv5b8YskvPqal7r/od4+q+d/7u05ggTQ3FEYSxDH5RJAXCVYKBB42nTAfCMaTLfYOD3li+wJaaqaZZf90jvBitlabhNouOgW7kPGk4mRqyKxgPuxx7rF1Sic5HiekqUWWimyaoHzF9vYWF3c6xJ4F66iEwjpBpAWegKaVbG90CHyfurQ8fXGTbk2AAPtwnHueQGvHhfNnkEqwP5qzuxojnENaQykkmYNQS4rKUVWObz65S7MRMKwsf/zXd3jjR29y7/pbtLurnLn8GM45evfe5O0f/RXFfA9lS6h8pidN3rp+G1FvcvnyFqWTOOdQAjpSIhELQ7PCLZoSKklSOtLcUCE5HCSLklVfcfvWAbaCRncNTyoC7XDKI/BrRGFAmRekSYIRENfrpJMRne46AoH2AmrtNo12HT+Q+FrQarfIS4MTljzNiKNgEbquKrKsZDybE9ebSCloNBu0VjcXrx3XCWNFaQ3OLVIJnzb9fNnrz5fBftq05NeSX0t+LfkFv8G016Pe/XwUslYgpCDNCqbzFIRA64A8z8jTGdL52LLEkzAeDrBuFakVs7xiXmnu7Y/odiw721vgwHg+J+OMd/bHnJwmjMYTnry6TS3yMaVhY71BmhpODaxtrSJkxlMXVtjuxnhAUdpFhYBeVHHkBooKLm20eXa3w2YNQlWxsBzTZLnlQW/AZG7REnr9IdPpACFhmnbACSIvQsQBvfGUlWZEhcNVBU9vNRAC7tzNufnqDd763n9ifnqb9GSdWOfkZcWNn/wtdt7DkwqtfKz0CfyIB7fe4vj4FrfPnWFr9yxWQD2KuXrpPN1uTFo4Tk4nWOeI4gDl+bSaEQrHRreBdAub93Jnm5d++Da39gacvXieM/WYoiyJ48VOaNgbkGUJlTEoz6fW7iBNhac9wkaTqFVjY3OFWuyTzKaYMkUrj7O7W0zHU1qNGs5WFPkcqTV5aakJRZnnrK52OHflMtZ46CAkCDXWvbth+uj64fz9tMendRHySdeSX0t+Lfn1X+uTxK9P9Jmfj1oCgcAym005PemRzGdIJ1BWYF0FEsosRcw9zHxGLYqZpynWwSy3HByNsGVJ9PQVwjjA+BFHxzMGoxnj4Zx8NuPo4JS3WwHbKw1WVjpkuWC1FbGx2aaY9ri6VsMXCmMtlbAIUeF5IbkRzLISoWAldDRChRQlpQNrJQJBaSTjeUmV5nz92cuc22iBFoS+ZlaV/G/ffoWzl64x7yecnPR58OYrbG6v89wzj7HXCJjOSr7/8m1uvfU2QdSA5hr5dMAbP/gzXFmgbL7o4mwDJB5Casgn9G+/zHx2yv0f+Oh6B2MdUmu6nTab29s4HXDSG4IQtNfW+Z1/8k+oX7uMtQaHXJhzaUmrGfPVrz5Lf5JRWCiLkjCWRHGApz2yJECOJEI4lPLxgxhnSrwwIq0qap5ipdvClAVSKOazOYUxrG2cIQwD5rMZVZWjlUR5Hk4oRuMp3cYiz3/m3FkO90YYYwmCAPkwZPzxnc5LLfUzLfm15NeSX++tX0tX90cZ6v1VGgO+uyp9v+9HOEGFo98fMRv0MMkUky1W4OBAlFhrsCZnMhqR5Yb93pQ4DhFSUWvWCGMfJQ2hrxjbiiw3uMpCmnBy6x2yYYNkPufM7ja1ZoN2zWNnp85K00dXm9RdSVJWOCHJjMX3JVSCtIDSKJSxlHnOINMUzoITFGlFYBM2N9YII83T6y1WAwglZBaqMsf3QpQK+du//QnHB/sc33qd07vv4AcRrzz1HPHWDl6ji1QBT/3W16gK6N27zeH179J/8ArKJpROgPIxgHAGZRzl/HSxw7QVzmaQlCgnwDhGwwOGd65jpYcFhJT07zeYjwYkf/Df0F5bRwcRcT0kqmuSLAMpEcriKU1VWsIoREiwtqLRqjOfJRhT0W52GJwOmU0mCLUwUdvYXCWOQ3rHM2azBIGl1mgghCRLSwazKb2jQ7qrHYK4gXULJ9ksL8lS2N7e5vBoSlmW4CTWKUCCeDdp/unRpznV9cu05NeSX0t+fbL1Yfj1kUR+HvVBwkf9mu/rtR3gHFYoev0x+WyESUeYfARuMZgci8Z8Ukl8P+DWvUMcq1zeifAVbKy3iEPNOCkhcpykBfePxgyOTxjev8/pjR+T+IJiOmY+zzhzdpvda2foxppQgJCaWZLQH05oNBv0xvPF5JlYKitoxD6RAq0DnFJIZ5DOUUpLhc88K7HW4oRiXFTMrKG0IAKf+0cJDw7GHBwMGd67xfHbP8BWKVpukiYlOxsXqW9u0qgrrJPcv3OAbISIKEI5ibIszg3YHOEsDotzCikXOXLrWPSpyeYoqRFItNJYVyFciRIa4QJUWdJ/sM+f//G38bvrvPDiF3j8qUsMZzn7h32sk/i+TxwJpBQURb44fIgg9CPiWkAUr7GyskLlDLkpKYuCVqvO5tYaZWXpnQ7o93qsr3eI4xpZUtDrDUhmM44enDCbJTSaLbzAR3mKsqqIgga628ILFUYIsjTHuHBhQO8MfArcUf++V8zP//uz3Nh0ya8lv5b8+vjr/fDrF+lj6fPzqPVh35MQFiHUokw0n1OVE5zNfnpozFqLkwtL9jJLOT48ZHOjxWBeEHqSOIgRAh6czrg7FRzPDcOkonIVVZEh8ymz/hGldbRXV1lvXqUexWSl5bg/YzQeMRueYitLrZFxNBhx4cI5/FBgnCQyklbTo+WLRQdnIVHO4rU8clNjlFn6M8fL77xDOxI8f2mLbrvOXiL4m5dv8+BgTJ7MOT24SZmdEje7nHvmRZrnnyNa3+TK+TXOrvucTCp6vTm+X1/0k1EaRIiUHjiDwCKlxlpwQoAt8JwBZ3HWQ2pNiaYSEikUnnAoqVF+hPYbVDqisnD14gV2z5+jqgSzeUGeOsbTKUoJNtbbdNo1hHB4WuKswxpDu1FjpVundA5dU6xur5ElGUopRvMMawuSLMdYh9AhSVZyejJieDqgylKEs4z7A26/fYPu2hr1TgPdquOUwPc9bGVwsqLIU4ps8XmRj3iALvWx0ZJfS34t+fXZ0COr9vqoHU3f7yHCRxmKts5inWbQn+BshRA5jhJrH5Y+AlLG+EFIOpswHgTcvn9EIUJa4aI7ssQxGM8Z5inDzFHgo7RP1FjBrzXJJ/eoewZlSnq9U+I4QJqS/f1DJsM+/YO7bG5t4YTDej5hY4oTCbV6k81GSDOUi1LK3DGcJUTKcWalzrwwvP1gwCs39tEKvvTkJc5tNckqw/V7J9x+cESRTJkc3aScHBAIQARYHUMYsbMW8dy2YqMtiH3FzVrA9aMDBr0jZK2NX2uyfuYS3c4qeZnR7/cpywpPK4ZHD8imp2AMut6ls7HJ1tnzZGVF7/iEdDoFU1IZi9ERwo9Y31rnqScfo9MKcRKEqmGcoigNlSkBi7OGsioRzqMW15jNEkxVkSYFszyl1YjxV2uMhzOGwzF79w+o10KkVIRRDe3FzKYp49MBw6MjpDMIa9AC0smcmR8hfQ+lJZOkTifQeGHIaJwiXE6a+5+ZCtEPFGX4BGnJryW/lvz69OvXVu316wwBP2pw/IJ3sciKCs1wMFmUVTqwZpFLR1hAIFSAEB5FmoA19Hoj0vIuj19YY2ulQ17mzAcZ05nDVpIgkOgwJvMDvHobS8HpvZ9wdHrMzXce58y5S9jKYYykEfrce/s6xw/u0V5dpb21y2g8RXkBTniUZYx0GoPmaJjw5q1Dzm91iIOQ/cGUSgds757hylaDCysSbMX9QcGdgxl5WpL09+g/uE6VjtAoKqMpspTdjTZPXmiz1VJoCZNpyt7BPfJixtkr19jaXOfyE1d5/nNXWe3WSY3lsDelcgKk4vDBgKO9fYb9Ps99/mnWNrq0OjWSrGD/YMBpf0I6yzg4OGI2myNwPPH4FdY3Oki9CMZrDb4v6HSblMUi/A2aylZQWlReUVQWIRXzLMfTmtVWTGUUiVJI45iOZyTDMc4ZWp0OprSc7B1wuncfWeQUeYEXBijPI50n1NsWpQOUFzBNMiIVEtUbnI4TkizDWodFLDdOnzIt+bXk15Jfnz19otNej2pX9p7XAXleMB6NsFWBM26RK3cW58DTIVYGJFmJpyWtRgMZhVw4s86ZM5vMswnD8YTBoOD2O3dpNldor63TO54xHs+58OTzZP23yI5voCd3Gb41YHz7FYKgSWv1HCelRdqE3p17yOo827sX6R+d4tcb1JsdnBKUwHQ6xRUJT17epNuuIT1B1GwRzStWNYhqjpVNRkbz6t0Bh/dOmJ8c0H/wDlWe4Ic1bJagfR+v0cUpxeFgihZ1plnO91/bwwsi/vm/+Cc8e2mddstnte3TjiTSwdxadte7JJUgd4Ldsx3m6QWytKRb94l8QeCDdT6bKzHJQ+v5/d6cvMjoNCPa9QiQJHlFVVnSrMRUlmajhqksVVEg0QRBHWMKpkmKqSxaKpTWRFGABOazhMlwRJ5mKCFxpiLLCqY6YTwYcvv1V5mfHBBqhQ4jpOoQNxpklUWHIdLzkVKTpjlVPaBWr9Nu59QCwdr6KgixSBt8CnLmS/3XWvJrya8lvz4bWpa6/0I5yrJgMhkswsYIpNBYSpyUIDVB1CCMGwiXo7Ri68wW22fWmaQ59+7cJwxiRqcD9q7/GF9CYaHIFGFnk6cf/0MOV85ycPIAJS2uzFAYqjxhaB3nrn2O8eAIezpk2vMZnRwjoiYrtSalqZgbx7hyrK02WO/WyCvLOLdcP5hyb79HHAWsrDSJO232546375zwzv0ho/GIk94h3TPn2Nj+Ogf3bnF8+3Waazt0NzbY3OpQa4QM05LZNOPLT+zQjDy2Ox6rscRXjkBaFIbSKoSQeNIS+YLcCnznCISg9D0i7Qg0aGmRQuBHgmYkqBCstprkto6nQQnJdGbJComtFk4UQQAGi1QOz5NMp1PQCq0lOEcU+A8PdlrKskQqhRUgtCKIIzA+rvLxw5iyMqSTGcnglGLcJ60KomYbIxVxp0NnbY3SOnqnfeq1M+R5hrMx7VaTTrvL9lqTMysOJZa1okt9UrTk15JfS369lz7Q4sc59yvlxt+v/fsv+t2jdkh97zeweM6yKskLsxgv0sPpCukeltbpNs2dqwirqKY9fN/j/NlNup06h70hRobMkpzR0T7F4IjSlKAi/LhBNn7A7Z/8LePeHgKLtQ7f96iswq+vsXn+cSSSZDzGOUdepEwnfTynGRwOKCtLGCiqyrHe9gldgXIOJwOM1Vw6d4b1VoDFsH86Jy0Vczzaqy064y6d9X/E5vYWXtRk6/CI7/91l8tXrvDiN77M9maDCx1NJxBIEVJX4OHwPQiEQ/GwjNY5hARfglKSwEFoQT68d4lweFoR+CCdQgmQLDom+xJCDWUpsc5hJRT+4pxCWhiMM0gF0knKwnB8cMR0NiFq1mh32vi+jzCLHYwzFdZawijCC0KiOFz8vDI4fGraYzqZYPMajVaXbDQg8HxAUOUlWvn4tSaTNCMQjkAL4igi8iQbK3WiMKZe1yTVDGMdWn46OgN+kPn4adCSX0t+Lfm15Ne7+o2d+fn15b5/+fO/VwhQOkmeWfJKLnZKD23DpPAQKqS9e5Wrn/sS9956C8oR1568wuZqEykXfgtlaRifHNHbu4PCoOodWus7zIaHFIMH3P5RjywbIaQECsoipbF6nhe/8c+5de+I+3dvEwtLJcAWFdl0Bn6bcX5K5UoOmiFeGFJKj4by6IYgioxzGzG+FtQw+EEIwufeqCQSHi2n2D23TbMR0e7UqVC02xGF+QoCyfFxn5UI1tbbrPmCSiy+MDwB6mHG2AEWgRVqYT/PAgbWQQlYDQUCUzgkFvEQHFou7rvBoZRYVJpYKI2gACySJC2YJBVOWmo1Hy09+qenDE6HaA2mKJlNZ3ieRxhFhGGIQ2KNxaQ5xkEUhcRhsPDWsJbhaIS1FVJ7tNbPYC34vsQLA7LKkeQV+eExXhjR7jZp1ENaDU0YKoTICTxJkqU82LvPF86cw1qQv6bE+d8v5/yo9Glf+PwiLfm15NeSXx+NPs78Wqa93lMLUOSlI7cCi8SZEqwFXUMFa0SrZ5B+RFEkrG42eerJi7RbLU4mE9I8J0syeg8O8LQGL2Jl9wJpaRj2T/DtnDwfY5wl8KNFoz2nyY3g+ptvMRhNqAeCcjpDYnBFQT6b4rUKCmHYaGxw9cIOm1sdirzCVDmB79Np1hhNcl5/e58zq00ubK+BNUSeJfA8Qiloxh3WGpqttTqDxNKbKtovXiPPSu7dP2R3o04jkGhhya1jXjjqviB+OGGccD/tjcdDF1n1sOeNUI5QOGpCUlqBsWDcItQq9cOy2nxR/SCFAmexzlEaRVEJZlnFcX9IrR7jhRGzNGEynZHOZwSeoBZFeAacqyjF4qAgagGPrEgwBqRw1KOAZj0kTQsmdpFbz5E01zepd7tY6dBhiLGOvdt3yY732D6zSSveIvQFWmsmaU6oJThIs4of//h1/ocXz+CFy2mz1MddS34t+bXk1y/Sh74LHzZ8+36v+1V3Vh9kJfie70lAYQ1OqsXgR+CUBj8mXj1HY/0saZJRzCfsPnGORsNHa4cXaHQQkCU5VWFpNrqgY3xf8+D2G1DlOCkQCrQTUOUEXkjot3EypCpKVuoBs+F9xqMTpBKEumTa36P0Q849/TzPvfA0F3ZXadQU48wwnxt6acXrd3q8+sZ9hvOEzY0mXyWiU9es1z0kElf3sVax3fIQ1mC0o4gk2ysNhF2EoD1bIqWHFQKHwOBwTiCtBfWz+/PQqwvrFlRZLPIdWgqUACUWjqy5AWMtfiVoxAKhFNZBZd3iNaSkNDBJS5xSnPZOEWId7Qdk84xknjAdjbCeoh5E1MMIoRSuclSFwQs01lSUpUVrTRz51OIAgcXZEiklSnko3+KFIV4gUb5P2KhRVYZkknD/dECWTjiztUIj9EiTOYe9U3bWWzQ6Me2gxtmzuyAXwPukmoR9liM8P68lv5b8WvLrk6dHya9f6xLwUVQ3/PrKUh0CQVXk1IKYmQgQGioJutYhXNtCRQ3mowlVlrG7s0NlIZkXDEclJ70Jk0lGvdXBCyyrK13uvv4yKhuhtcA5ibUgnAQUiAih29Saa5iyZDI5IpmfooKAetyiTCdkyQQxm9DttFjpNgHDZFZQSs3tvRGvvXKLvfsnGCCMAioH/axisxPTkeArgZOGQEFTlRQIIk+jC3CVpRXC5m6dwBqUswgEIRLtCzzJYuIAgkUoWQrBu7dPAM5ZrLMYJMYJskowzAVZCUlWITFsr0REahEOrQxoLbBSYKyjqiqiSFMLJAf37zKfrxOGNZwThGGEdAaDozQVxlRYKYmUQmqP2TRZnOkIwHqKqiiRWmOMwyGI6jWk75NnKe1ug6gWIrXCWYE5v0OoJVvbHVrdJpGvSWeGwWBK7Dk2211CT/L01UuLw4qYRzoGPw76JDUk/E1pya8lv5b8+njqw/DrUxP/+mhgLShKS1Tv4rUdcRST5Ble1CDurOCEoD/o09pYo7WyTpoJTqYZ9/cHlE7TbLWZl3O0L5kMTkgnE8K4hZMBwglmkz5ahQjtIf06Xn0d69dJp32k1qzsXOSpZ5/ljR+8RFE5wrhF2OggtSQIFM26R1ZKDg7mfP/v3uL+7QMCKYlihWcXB+0ms5yiNFi58Pao+ZJIg8LgpIdTgkluSEcZVUtzecWnESgUDmEtHg4lFrvICoEUP+ujIt3D3ZNzD38PmZNMjaSXw/2R4WhmSAqYJxmYnNJK1moQ+hqHRFZucX0FtQCCSHHl/Ar/+t/+kC9sbGEcWKmIGk0CHCrwyauSk94pCEmnu0J2cEyW5TSbLUzN4sqSKvKoRTFJUpIXBWEtxotq+IGgFvsEgcY5R7NZQ9t1PM9jda2+MCETHs44bCXwvADfEwSeY32tgZbuM2ESttSvV0t+Lfm15NevV7+Sw/P73eH8Qwfy/qFr3+9zf9DX/3ASWKeYFY761i6PX3qG1bVtRsMBk8GIc1evIoOQzVZILSqIu136o5TTWY7zPZx0jCdDpDHYwjLcPyDQMfW1NZpb5+l2t9i/8w6z4Wix21AeW5euoYKI2ek+3/jaC1y4eoXv/M33yIzh/JOfZ+fC4+w+/hiNrTZOCYaTkllheO2dQ3IRsrK9RSjAGEPYrBGvdDid5hxPEvx2SGwtQbBo5GecJrGS3sywdzpjME6ZzH1MWbIWh6zGktgTKCGwWGzlkEIiJEgcnhRosYgiW+cwCDIk4wrujQy3hhV3DqdM05zcSLLCEGpHt1my2aqhtcA4qIpFo8Qw8NiuR6TG4V3a5PGrFwkiH3RIkgQEgY/vLIEvmE4mnB4dMxlN8D2f+WxOGMas7eywtbONDTXOGrLUkBfVw0Z+FUppojhEaY0UEuUplDREtYCwHi5KTS1kRclRr8f9uw84s1FDSkfkORp6cQDS8clxSX3UKZZPupb8WvJrya8lv+AjOPPzD/3uvf79ayv7/LASllFaUN9Y44knn2FjtU2elxRpjvJD4lATsMFsOgDhczIec9AbMU9zJoMhRVpQc5bBvbdJp8fUuptc+/zzfO0b38SqBn/6pyH69IRkltHe3uHic0+jlaJh53z9S48jheP0Xx+yubPL13/vd7n25DVKLclcie97pKXheDgjE4p6d5ViNIJsTprMEZlP5DTjWYZhhfsnM86sNWlZiy0100qynzjeOsm535txtHfELZNzvVujHYdc2u5ydqNDqC3tWBEpgVCCoqjAGrpxQF0u4OFYBFIrC6WFtLKMZiXDeYFwDozF0x5+AHHos14XBMC4gKkVlJUhjjyMgVliKZXPtRee5nSU0+nWEGIB4Go+J8kSsqxAGEs5n1KaijJJKCxUyYRIW9obG6RpgXOS0NdIZcmsQ3mGIPApAU9KvCAgLw0OS60eoD2J53kopdFKopUB6yiLCuN5COkQziFwn9ic+VILLfm15NeSX59tfeQOzx8bEHxAvVsOGYaaC2fXuXxujfVWSJYklGXEKDPUfUkz9DkVKQf9KccnQ+7fekCeTDFFgawK0mzCaDQmiOu8+OLn+KM/+qfIRpNbBzOamxtcfPopTnsjVs9sEbfb1MMQmY04Gs3xMEzGp5y9eJGdxy4yTFOu39jjiSfOEsVzuqtNPNVknDrKpOJuv8fpvdtILFtXruLKhM3uLmVpEeWidHVeKKbG8mCUcrefc/doyv79Y6YnPap5yokf4NUj7h6MWV0fEmjH1d01ntrtEOpFrjxScrEZcYtOulIKxENvDKkEcezR7mhamSAvK1QlmKc5RZmT5jnG+HgeRMpRabHosiyhcoKyhNE0o91tU5oxzXpIkhVUsqKaz3iwd0wxG1MmCb5aHDSM6y3KLGd22qN3LyRPEozQ+HHEymoXP/QwxtIf9pFSsra2ipQQhD5aS4QGvxEjMUjh0BIuXTiL9jwaNQ04irLChT8bG0t0fDq15NeSX0t+fTb0sTzw/HGRw7K11iIPAkaTId3GCnEgSYWkJR3NUONLR1EV9EcTTo9OyUZjZv1DrCkwVUHoGbI848Xnv8g/+71vsNWO6FcljoLHn7yEV6+zdnYbGXnkiWE6HlJlUypb4/jWLZJZQWdtm9d/8go/+v4rKFXn2k6Tc+e3iAKoYsV2p85wkLCy2oVshsDRXGmxu91hqxujlaDdjGmFCodknjpGiWVWCqbTjNnpBJsWCLs48FdUjnlmaVvNar1OoD2qymEFhJ6kGS3y7tqBEItdhBAPzcEqKIuKKjfkecpgWiCkQgCe52Eqyzx31DQEykKsMGbRcM84R+BJtBR4QrK7sUJaLspSK+sIIp8oDji+e0R6eogvLcYJVK1FEChcJTneu8ew38ertVjZ3qbeqBM3IvI8AxxSq4XJhZBY6wg8hXMCrRRKaBqhxpMLR9ZLZ7eYTfuYqkRGMQ/3TEtwfEa15NeSX0t+fXr0oc/8/LpKOX9Zbv3D6JddL8TCnlyZgq12DPVV3nzQxyKRwhL5iiAQeMJSFJZZVvHgwT53336D9LSHKeZUpkArC9oRhh5f/PxznNvdxBrLdJoSRx4bcYMCQW7hxp1jegcDujWfnbPrJGnBO2/fgDzjrZd/TH9wSDKe8jvf/Me8+OQu67VFuWXDk8SBRnmK+voqfiNGaUV3Y4VzZ9tsdSMoC9ZrmrWawAnJvHIIaTECKmfxA595IvHrtUV/mKhOvdUljCOkrFhfCenG0PAX1vCRBv/hVDKLOgmEW+TQQwXtSLHeEgynmtCT+EFAFPh4rmKrpalFAq0Bt/CgsAqMcVQVNEOB7EbkmQErMabEWANKEMYhG5sr7F2vMOmQokox1lLO+yA1SimsdczzhMhY9NYWzjnm04QgDFlba6F8H9/3QSwqKay1SB722GGxa5Ji4fjqKUGhFFp7CCkRSCQWcMvt0ydUS34t+bXk15Jf8AlMe/0q0Hm/zdx+CkjhMUkM908HDMc5e0cTOr6j22xilaSSilmV0R/OGB6fMDu+Q3K6v5hSQlC4Ch141FpNmq2ISlp6kxmp1Xh+gDWSooQsLSlmBZ6A1dUOW+urXH/jHU72H5DPBuyd3iEvDfXOGo899RheoFDCIVn0lAFDFHtsnFkFZ8lNhaJivR2w3fKpkoK1uqTuWYx1NCNNqxEixnOwkKQZZQXOWpywBGFFtxuy0tKc6/qc63isaUcoLQiHtG7h6vrwfi7qHhZzSWpwMWitCEQDhKSylsBTCCPphJKWD0osPDKUXZh6SSHwnMO3oDHoUOKcIK4UzcgjVQbPCcI4Jqw38cIm1axCUCLKksrOSU2BFJIgaCKrGvNBj7zMKZGEtTrrZ7ZZ29pASEVlHWmagyuoRT6BpxelrtaBkhhnCLTED0KKypEVjioQCN71yXhfQ+mR6sO4pb6fEtB3q1+WWvJrya8lvz4qfdz49akpdX8U+j/eQEElfF67dY/vvHLMPBe8VY958onLXDnfoKIkTWZ4EgbHp5zcvUUy3MekhxhTIGQACPxwHS+qkVvLMMm5fzLFq7dohgJshfM8rAq4dnmLuO4zm6XcfOsO119+BVmWRNpnlE9QTqOV4J3bD/jLv/b5p1+/RhBJSudQ0rLVDQl9j1BL8qrCWsNq5NP1BKruE6oFaLQWNBB0Q59IpdSigFanwSDLCaOQ9nqDJ65s8YVrG5xp+6z4go6CSDikAuMECIl4uGPioVuqcAKFw3eOmhTkErbqkkALysqhPVBOoQVoYXHOoaXCycVBQ+PAWoE1kBYwTQ2TyRwlfUKtqQqLKSusEOxeeQLhNLN+D1FlFMkEOxshrUUKsKYim08Ynp6gkzlha5VchYwnM9bPbKEDj9BXaCxCWJAeRWWJfP3QFI2FKZoTlEIxn2ckpaHTclgUcnlYcKmPoZb8WvJrya/3r1+p1P29fv5hdk+/jjD0+wl5//SxOJy1HOwdc/P6m1Slo7W+S1Rf4WQ4p9P0uPbYDsI6jvfv0XvwNvm8hytnKFdhTYn0GnTXttD1LrnTnIxSDo8H7AY1AmnxQ0XgafJZiVcLSNOUNMs4POqRTKfMRj3y0RHGlAhXMRsc8dd/+h+YHH6Bi7vbnLu4RlEUbNQ8NtohkQTtLFb4VEJCWaKcpOZ7VHbRkE+y8LRw1tGIfTZ3VnAagrri0s4mF86ucnUj5FJL0tQVSggU8qd2qEKKd2/QQgIqu/iZdeJhUFVgK0ukBb6yqIclpgKHdALzsL+OYhGiLRHMC+hNHYNpST8RDIZTfvzyj9jY2OTchYt4wiNJZ5TWsLazs5jwaUqVJsyHp0z7J6TDHnmeoKTGixpEjQbS92k2GzRWVtk4u00YBzhnqKoKpEBKRWkszhi0dGRYKinJsjlh4DPNMsZJQaA0W5GHFSES8bPP/xFrGZF5tFrya8mvhzdooSW/PlJ9nPn1yBubPuqw8aO4eR/2OSpnmcxKinRGOhlTJiWSgKe/9AxfeOYyba/i5r0TBr1DTHqEsFMsD3cWUhK0V9m6cI20Kkmt5PbRiN5owtUrHrYqyYDhxHJ/f0xSOBSOVrvOysYG+zfvEcUdzGQfckPlclwpUPM+t27e4N/8xcv84R/+Fk9u1zijFjsYIQXCSnILg8oySCpmxsMKySzJ6dY9lIDB3DKaZax3YiwCs9Li6QtrPH2mxnZNshZAJCxKsthZCLnIkAuHfBgyFUIsYOEEpXRIIygfGoXNc0tZOeqxxOEwRiIdhHphsFVWUDgocfhaMi3g/thx+yDh7u09eidzTh/c5OTgPuf/mz9E+RKTG3QQ0gxCtFJkKzllHuFMm6jbobm+zfjwgN7RHlJAvd19CA9JrVmj06kTBhpXlSAUxgFKIKoKjaUWB3hSIJyjKAtmSc50nFHvhCR5xlH/lC0vwO6sgXu3QHapT4OW/Frya8mvz54+Ep+fT4sqa6msxVUGZSyqKpgc7zPurTGabVPJgtl8ymTQg7JY5JLFohleJT22zpxn4+w5Tk9PEEpx2p9gUZTWUuUVo1nKIBG8+aPX8LTP1tlzpH5ENs8IFHhaYIxDCImtDFBR2pJJmjFOK15+/TabjYusrIV4VuCEoNKWslTcPZpzmlTMC+jEHkVR4cchVWEYJDmdVsi0NDR8aG81OdvxONsUdLUjFGZR/ik91Lu+EO8ekgOkcwgswi1e01pF6RwpkFSC4bwiDBSKhWNqXoKnQEiBM47SCFJjMc5SZYIH/Yofv3XC3t0Dbr7yY8ppTjo6wY891rsNosgxm+XEjRiJIEszlKfRalHGKZRCCYWtLNXDTV6j3aHebiMkeNpDeRpTVWinUVIR+h5RGGJNBaagUQvw5cINtiyhDHxu7B2xUtRwacKDN3/C6rzB7z+/yRIcn3wt+bXk15Jfn239SpGfDwqQX/b4R+F4+sjekxAUpmKeJHjaxwtbSB1TVYYH9/Z47Z11trshyTxlNBzinGBxdK5Cao+g3uLZL3yBy1cvI0RJo15nv7dPp9NCkOGJkI2VFvf2bnP/9VeotVqLnjajCUe332L/te8xP7qBMvNFJ2Yn8JRCCkkU1hidTvjed39CUObMnjnL0+fXqPluUXnRz/nPP3iLUmg21zu02g08Dc5zVHlJuxXhJIwmM1ZrMe1AsRGD72CSWoxvqYca6RzSPQSHEA93hYvDZYLFgT+DpLSOospJhOYk0dzp5ZzfiGgFkJQwLwyRr/CsoLSCk9RyNK7IShgPh9y7d8yrL7/K4M5bjO5ex9MeFZK4dRnlecSRR6PukWQlTvqUpsKPQjypyNIU6Wl0HNFQHrV2E6UEQRwhlMYYQ57Msc7hB5pGHKG1wNcST0HuFnl6KwAhMdZinaCoHIe9AZPBGJuc8PK3/5idb3wNYVk4rr7bFXGpT6yW/Frya8mvz64+NpGfDwuOj2oH55xb9JYZz/CDBkJKjAqpN5v4tTb90ymxMkz7A5LZDCl9KlngrEVKjycev8rzzz7Bzu4GVdInCj20sKw2Ixo+hEqA9jm8eYO09wCRT9hHsbZ9nuPb10lObqPMFKqcyi52HVp5OBTZZMrp7btULudPDvb4zl9F/J//T7/N73zlWW7vz/j3f/Uyr7z0I6yT7D72GBeefo44DsnTU4SQXPICrK0waNqRohYIBnPHjVGKJy2PnQkJ7KJ/jsBRCbXYERqLlQrpwBOL3Lh52Pl4WHqc5oJX3zjklbfu8Y1vfo5pIjgYpYz6I9bbTWqxxghFb1bxxvX7JIMhh7fe5vjOTWb9ffLBPjbpY7TC+W2UfozJtECcTGjUYnr9U6ReOHWFUYSpKqTv4QsIIrC5QbgYz1N4ob/4AshLHA4v8InjmHocIYXBU4uKDaMEQuqffjYQFMYxSTJyUzE97RNlR9jkBG0N1lWod5sFLfWJ1ZJfS34t+fXZ1se+2us3AY53lSYFeQlOhzjlYTyfxuYKTz79BK1IUA8Mx/fmaB2A38JpH+kKlNb80X//3/HMU5cpK8FopU1WVQgcDV/SjUKc9DnsDbh3/Tr55IQqn1MP26RBDzsZoaoCa8GisC5DIBAywDpJIAUyHZCNDiiUoqd9/j/5gHfuDXnztdvceeNH2HkPKxVpf49Qe9TbLX58/xbr5x5jOM0RCra3OrhxSh/FwfGcGzfu0/TB2Itc3m6wESkaqgJTUQqPxEiKwlLzxcIvQkgqK0gqwY/vJNw5nPLn/8v/SlFZZLyCMYLjOze5/+bLhMIQRgFBLcb3I26/+SbV+AQzG6BshrMZtkyxVMjSIZGMD27znf/13xLWa3ztG7+LF9WZpRm+5y/AoRRSSnzfxxqDcA6JQnkSHT70zXAWL9Dw0PvC1wpfKzzlUHKRM8cuKldstTC/KCoDSMIwZFadIrIEW8xRwqGkxFn3a3OH/zDlob/O51vqF2vJryW/lvxa6OPGr4/94uc3KeMkXlTDKy21ZpftS+fYOtNle2OV0JU4mzHPCxorO5R+m1A5TDHj6tXzfOXFL6KkYVwVdLsdru+dID2JciU+jnGR870fvMyDWzcpiwlevUmr08GWGeV8ArbEusWE8MSiRBHpo8MaQjnmkwPK2SFCWqz0ePB6j97dO6RFhpmeQjVHCMlweshP0kWuPisNk1HO7TffIe50KF54mnqnTm8w4/6rb7L/2g8p84TrP7rCc1/6PM9dO8PT59o0fElqYJCWGCtYb2ikL9ECysqxdzznf/lXf0zvYI/9175LbeUsB29fpsgK7v/gT5jtv4rvSgohsVIiK4tyAi/wcVWBkxZrzaLjMhLrgHLGZO8nTI5v4IdNZkd7fP2P/kea7XWMdeR5jrV2YfgFpHmKrwOscTjpUL5eeHWYECEkzpRUZYGzFb720FKgFFRIrIXKmIVHhtBMM0NaOKypEFqAXHRQVp7GOZBC/mYH5lJLvQ8t+bXk15Jf761HVur+fn//Xo971DukX/0aQVFa/Cii6dc5f3GHz3/+Ks2aRjlHkVTMUkdzZY2tq09RJgV+EDI8+d/Z+68fy7L8zhf7LLPt8Sd8ZKTPsl3Fru5mGw45Qw4G1BhoBOnqQoAEAXrVq/4AAfpHJEDSg3CF+3JFCHfmzgxFDptNNtm2urzJyszI8MebbZfRw47qbhI0XcWq7jLnC6SNHedEnLP2J9b6me/vmP/mv/lXpGnEcrXA4QkjRawVt/b3aIfgcZxO1vz4xz+kXo9J2136B7e4eece7772E7yv8MKDr3DeI4nQQUTU2SLdfYa8LPBVBqGizGdNCNMajCuoqxW2zlG+8S7FF0ye/BTvFUl7l6t3XkXFLY5e+m3WucWGnvXK8uStn3H12nfxtmB8+iZPHr3JD+484JWvvUK338FXNafnI+7cv8G//p1n6AcS8CxqwRvvXfDm9/4jq8sPUNWKxWrO+0VFuZpRzt4nsHOkEGiVYL1GKYurLdZaKluivEKpECUkti4RwuGFIXQLfGWwVcXpa3/OO4cD/vX//v/I2niWK4GxHikFxllaSYTSAUWWI4QnDAKEkAjlCaIAJTQIT1XXWKPRWiAlaCUpgXVRNxCRlkdPrzh/csJ8dEmsLDrpEvdvceuZuwitwdmPvLY+y/oyRYA2/Nrwa8OvDb/gcxD5+bTB/PfZzwshqK1ja3dIO95ja7fD3Z2YlnKUBi4rKPKCVrvLzt17eOPotrscTgf89tefZ1EZrlaOvCiIE83+IEUIReAySqM4PpmwmIwRriRO9rl99xlu3bzJz77/p2itqIXGe4UIQqJ0QNIdoHsH3P/qNwgCzftvvsrloxA5ldi6QIUdhBIIlyGlBmPBS5wQCAxSGspiip+f8sLL/5ZkuEVlLf1Q0ooUu7t7XAUBtrxATBaMZxdcvf4j3vmz/wIqoDCWw+e/yvMv/W8JtUADufW8f1byF//1r8ivThBoZPuIMGw1g/7KBVIoXDjE6ASlOyRhSJmPsW6OxaGCGO8EiOvTidR4V+EJcMIjwx5B2MGVC179k//E7//hv2H7zj0ClVBUlrKqcVYS6AApJZVoOjnKdUaStpGqcVqN45BIN3/PS4tDYYUky0pK4Sitp64tk+WKrDJ0uz3Gp2f40BF3eyTD22wfHV73STTh5c+7Ns7On742/Nrwa8OvT0f/VH595jc/vyl5IAgDHjx7gyLdQ5iSloRBqLh0hotFxvHZGcPeNlEY0+922OrGDFtHeK15erXm+GJJK5QctmLSUGC9pyg0r771lB/8+V+zvBwThCk60KRpABiiKKRUATruIoOIsNUlSAbo3hZxt8fvfPM+zz93i9dev8f/+Ed/zOWjFnk2R8oAs7xEAMI3vhkOECJEKoF1FdgCqjWrVY7IC8JAIhWUdUnlwOmQSji0kEhXIH1OORsBmqB3wLe//TXu37tBrAXWOdYIXn10ybsPL9i+/Q26B3dItg+4ee8us8WKD177K3S1oDfcYVXCKnOYfIWfnaHKKWEU0entsJ7PWF89Qpo5QhpULfAEiLCFSnfpDPYpllOMdfz5H3+Xf/9/uEVeWSygNFB7yrJGC1BCkGcl1jl0ECGFRGpFEAQo0Xzdq7JiUTqKMuPi8TlBJ+HmnRtEWqN8SSuOCGPNaRTgXYkIYwZ7+/R7/evOlWt4fP75sdEXVBt+bfi14dc/rI+0+fHe/70njX/oc37Vaz/KNZ/GdX9bgRYcbrWpO11GsxWZhRaa0brknccXFOMxf/DKc/TaKe00QglL7Szna8PjqwWj6ZznbuyCE2S1Q0jNyWjNz157n8fvvoUtV0StHiKMaXdahHGIjhOi3jZhu49UkqjVA53S3tnm5Rdu8Qdfv8VOP+Cwe5u94b/nP/3xkPk6Y7UqeP8Hf4LMNdJJUBE1ISroIYTG+xqtFFK2mVxNSXdzkiSitoLJ5RVn7/4UPz8jcoBzCBngVYBTGpAc3n+RF3/rZbqJRgkonORy7alkwrPf+QNcmXHjmft0d3qA47Co+dZvv0C7JQlbEcdnKx4+GZGvlrS1p1hlGBTtfp/1+Io3v/fHLM7ex5sVOhF4NNtHDyDexgctVHvFME04vVzyxuvvEe/eZlHktKMAvKcuSipjWa/X5EVGr9/D1BalIQw03nlKb/AWMJbRxSnvv/MWo7MRd1/6KvsH+7QCwf6gzbqlWE3nCBweiYoSeltbJEmCsA4pGyfYX4c+jcjBlzXas+HXhl8bfm349aE+9cjP5xe0nkhLhjKkUIIL63l3tObYe374+kPef+8RXz2MeLAd0ksFVhjWRnI2rnj7cs14ntNLIwadlMl0wbyUeOE5n6x4fHzMYnKGFpaw1aG3s8fB4R6X8wlECbdf/CqL+Yra1PR39giTlLvP3eGfv3zEQVuT2oK0q9n67V2evfNvGRvF//d/epWTt9+gKHKErZBhRNLZprd9xHy+ojPoEKQttEpp7+7x8tdf4O7tLcbzinqxZn15ibIGL0OE8oioRzi8zeDGPfKy5Bv/6g+5+9w+adgMAVwbQV7Bc3d26A/7lGVNrxuTRCBxpDqlpcBrQMBuL+bBrT5eCrwRLFY1hTeoRJPPD4kjyezsZRAWD6zKmrvPv4QMYkoLy2XB6Zs/Y/rBT/gP/6//O//83//vqNMBPo3QAqytm5Zdpdna3kFpjcMRqqDJq1uDExIlBMViyqt/+sc8ev0nEIYMd44wpSOIHIESRGGIMm26/S6Ti0vCOKK/1ScM1C9CrV+gU9Mm/fX36/P7umz4teHXhl//kL6waa9/CrSEaDxBo0CBjNBhRCuKeHq1ZDnNOD9f0NGe5+/fagbRAbmFs6XlvcuMy/GKOIzo9QIW65wnp1NMGOMw5HnOcnyJzVYopYmShHvPPODwYMjT1x7y3Esvsr21z2tvvkPsDL3dXeJ+h+0be/T7HSQSITUhEIiKaDtgcVJw8uQEEbZIdm6j4gSlUnpHt+nv7TGcj7l955D+wT61VRzud3n25hattuJYSV5NIgb3v8oqTamWIwQQdIbc/9bv88K3fpeLy0vuf+UZ0lASy+t5OVLQTTxxIui0JJVN0d6hvUdIRRxBpMB5sLUjDBztgcJ4wXLl6GyFICVRohG7Q148/F3K0uCFoDSe6SKn1WnTChUGwV/84D3e+asr8tFjFusL3ugPuPmtf4M1HbwzBBqcs7Q6HeI0BQFSClSgoKmnxFqPr2uevP06T177AWb0CJd2WU5G5EWB2hogPYTC0W6n7N04IJvPCULFwf2bxLG+tsX3XyR2bPQZ1IZfG35t+PXp6hMzOfwkwsEfNST9ca77u64VCPzftvwWAq0FOR7jKmLtCYTEGE8SBnztxRcYbPUYrQylDyi8Y7TK8Uox7LbBlRjvOZ2uOb5cYN2YziAhXy8opmO0bVoPnTVIadnqpzz3zB0WleZytGDnYB/nKjqDAZVUzGZLslWE2+pSS4FCoJxBSMF0vOD05CnPPPuAV77xEgs0T59OGR4dMNxq8exWxIOjIVZJFplFKcF2rPB4Qlnxu7//Vb72ynM8fv8Dnj45YXoxxkvJ89/8Fg9evEOv3+X2fo+uhkgJAiFRocALKJwjUZLCeYRzhEJRWgHCoyTgBV4JlBAI6XHGkmhHHIcooQmkAOeQPYFQEdYLKgeHW5ooDAiAlYGtYZ/d/SPW70og5/HbP2b7+W8g4ohASaIgQCcJQkoqUyOlRApJXhYIAUEQ4SvLxdNT3vjRD8imJ4RuirQBdbkiqzKWWYtEhsjAYZxluL2FuH8HreDoaI+wiaA3vhobenyuteHXhl8bfn259YkPNv11fN4nqr/RHequQ4Kyqdz3kn4Ew9iy3054fi/lyWXC4xO4e5Bwtch4Olpy/2ibg4NtbqiAOFiyKiNmC0FdZ5ycXnJ2ekZV5bw0/ArTyzHlconDYbzFmorxaMx6vaLbSTl+NKE2ljhSDLZukBnHdDyjR8F2egNhDFY6BBJ17SmRZwXf/tqz/MtvfYVn7+8zruFPfvKUnf1tUp/xyt0hnViTl5auVpQerPNMVxVJqHnlbpuQHsVLuxyPcp48nTYwCCRxBAd7HdIQEu2JJISiMcmSgSD2jYeGNg6vJFIK6spT1Q4pBLXzeCFQWhFcF/RpIVGyKbwzTqGERAuBpLk341AQRgonPOIaJlESIqVGOIsxDqqSdqqI2glRGBFJSyttIZUkTpoiSWc9de1w3uOEJ68Kri4uMXmOosbjUFKSLa+4Orui0+5jEpDG4awnjkK6WwOKfEYr1Cjh8d6xIccXSxt+bfi14deXT7+xtNdnAhx/jxoXSYlE0oki4kgiBLhYcLPT45mhYrlc8PZkjtcJxxcTgiQmCCXDfgfmOaZUnM5Knjw+5ez4mLQdU5U1Z8cneFshJCAVTii80MxWBTYIOD05o6gte7vbSCmZjydMLy65d3QPn4ZkdUVb0uS1EWjr+NaLR/zOK7fph4JAglzUfOfBgO2tFFkphpFoTLjwBEoQ4shLRztWIKGtPLEWtCJoJwnP3EiwwGJVowOHjSWxNmjVnFKkbKYAgfiFU6jzWA/We6y1eCGxXmLctfmWliglCAQgG6BYrtktmpOI882vyEMnkBjRzNYxHoo8Zzk6x5YL0DEq7rCzPSDZ6VC7ACEccSumHcZEWuAxWOsQkaR2lmVZIkxNlS0o8xnOleAd0qyppme89cMfsL+3RzvpAwKLR1iDc5Zup0MoFYGS1yNxBPztk/bnSB+6pH6W78HPuj7Lr92GXxt+bfj1j+sLW/Pz0eT5cDE0xVPg8ZzPc8rAsBcExBoUDmFztsOClatJkphVLbmc5XAypdOJ2NrqoIRhpxsynsZgJavpmDja4eLsnOnkAudyJKCChDBpk/YGFETMJivOTi+QYcBgq89ituDq6RnGVuRlxZPLGf2dDm0HXjaD+WIpuN0X1M6i8DgHg1Sx1e2Ac+hWSG0MpXUEQhJITSw9/TCgFILCgbdNF4zzhpYSBJFGS7jVDilrS+kUReWx1oFu3EGbZk6HBLwUWCUpjcN6DyjyqmnjdEJRGUtA02EQCIFAUHuorEAJTyCbGgVjHcYLhHe0tUIoWNWWs6VlPJlRLMYYa5HtHXbvPM/B/ha9/YS3Hs6pXcDF04fcu3mLJFa02yFhIBEeAqHQUZtykTO7eEo2PUX6HHyNKefYyTmrYAC2Jg1jnDPkVYGsLWkc0++EhFqipcB792uzht9oo19NG35t+LXh10fVb8zh+ZN4jE/OVfUX8ADwzuOE5L3TMVuuRa/dRl/3BtZOsSxq8jyn026RLWqmC8Noec5g2OIZKbnRDZrwqvJMxucU6wX4fS5Pz6nyJc7ViCAhTDts7exw48YBo3nGZLzClBWDXg9rPRdnl0wvrkjaKY/eOebu9hZ3tocoa2lLR0sLhLcob9FSYV1A4QxOCpRwSNm4pIYKAtmM+VNSEAiFF4LMgpRQOyi8wKCbqb/Go4QlCSWxluReoNCY0mKUwAZNiFfjEd6jrgO+tVeUFmoP69JQ5xYjJHnlEBhasaKXaAIpqRzU1pGoxuDVODBOUHuPw7O2jkhJagQ1EixU+Zp4+zb3fuubvPiNb9IddDkYxnzvu6/x/ntj8vWSy/MZz33lGQ5kn3asEcJjcazWGe+/8x6njz/AVxnCGhQKLwKccQy6bdJ22oSYjW2mLRtPNwmxdYX0zXfJF6xT4rMcwfg0tOHXhl8bfn2EpfUZ18bk8J+ka3CID31AaHLmDi7Hc8b5GUfb29hWRG0dy9JzPqopCk/UarM4fsL77z/i4NY9psuycePEEQqH8jXnTz8gjALCOOXi5AkuXwMCL0O2dve4e/cGzz+4zbvnc5arjK3BFv3ekCqruDg9J9Qh1dpwebLgL3/6iLPFiqMu/Kuv3KXVCbAYPJLKBaxLcEiUgNqaJketJNL75pcQgMMD1lmU90RC4YTA1FBYMEqQe4dVnnYoCGVzr0gpyH0zNC+TilgKPAKJRwmPEXCZORa5Q2iFkJIyLxhlhtwIFuuMUEu22gm9TkQSh0ggkIKi8k1o+fp5PILCekQN0oGoPYurCbX13Hnl93jhm9/h3gt3idsKrTR3D7v8+LuvURWWVW+Lp6cTlvMVNw930KGgqmqq0tDp99ne3WOx2iavljjn8eEWundIb28fqZuQuHHNgEHva8qywJUFbEVIKX7eSfMF4sdGn2tt+LXh14ZfH0ebzc/PV4H/pf8QOOeRUnEynvNffvAONw/28EIwXWeMZnO2ugm+WPLuw4eEOmQxnXPvwQH9NKId1ABMLi+plkt2D25gvKdYTlHOggxp9Xb46tdf4dv/7KsM+gmjzPBUNjno1WLFeDSmzAsCoXBITAWPTsYUwnDvnz2PCkNK6xqbc69Z11AbSyeUREKC9yjpUTStjaUXWBS1BesdWgqckJQecgfzCpZ1k0evHRS1pxsLosCjnSUSEh80Lq81Au+apgEtmtPO5crzw4czrpY5W702RzsttrfaWG2QJRgZsVqtuVqWFNbTbwsSBaEIqb3HGEegBe24KYQ0FpyEdiAhz7g8v+DWS1/h7ksv0dvfIunEZKZiUTi+9e0X+dlP3uXdd6/wRcnD198h7oSkrZh2J8EVNVmRo6KQl7/1z/ggELxfOtK0Rdi/za0XXuQb//zbDNspiQSdRFTeUWYZdb4iTTVSgZBNh0izRr5cEZONPqPa8GvDrw2/PpY+9Vb3j3vdr/q8H/Xz//a1Hy6DDxeFAJxrZuN0Ox1efXTKa68/xhnPzvYWDocIA/b3dsirktl0Qehg5yBm0AppKUMrFBRWcfzoKVGYkPb6FFUzzE8JgdAxt+894Dvf+ho3drvMlyuy1YrpeMx8ugavKIqy8WTQDhEFSCvpRCEv373Dg/09HJZxacgrQelhVVQM2iEd0YRYpVBY58kNzAvP2njWtqbyEi0ckQ4o6op1WVMRMMs9WVWz00twUuKKmkgqwr4iEYIAj5FQ146itiipKJriAjIneO+q4I3TJYvKMs5qvDO0bm6RBoJ1UUFdoSVEYYBSGimbVtWs9FhnkdfFh8KDlgLrPEXtCUNBkoQ885Xn6PYTWt0Ww0GLdqpYZ4p15QgDwb/7X/4B/9f/2x9RLqdkWcXB0QvU3iO8ZHd7CNJzMZmQRjGmrLmaFYCkc3CX+1/9Ojt7e/RjgTUGAkUYKFZ1jTM17c4A1fS9Xs9N+nX5o37y+rKluf4+bfi14deGX58/fZL8+rW2un8WwfvhV+S9vP6XuzaCEvS2trl7N6AqLFfjBcvlmsVsxM2bRxw/fErlDNVsTpFnxK2YSN5jvx2CL5kXliePTgjbA2SUYuaX1MUKayxhK+X533qW+zf7RMIycjBd5KxXGfV6QbHO0VEMYYjzEcIItnd3eOaFI15+sM12DM5rjlcV0xyQimxVoJIEu66JZVPVPy0sp8uaDy6XrMqaIIpw1hHKAOfgfDSmcI44bTUBYOd5Eq/Z2+lRFjm5caxswoOuYjf2aAXSB0xKSy4hMzDJPLPS8sHFiiqvEFJTWUsYBAQCRKTYkxHdWFI7Gh+LqiZUnqpyXIzXBJGi34pJhWpMxQAnBKUxVF5hBDzz7E0GrYhuT5MEDiFByYBlYZlmEpl2+dbvfZ3v/ucfsHu4h1QKYy2rLGfYDem2Iqzt8HQ9Znh0i6//iz/k0fFTvvG7X+ferQPSWKMCh9S66ZPxipUWyCSmFcco5UA27rBflHPTZ/F+/E1ow68Nvzb8+vxp0+31iUjwYfxYXIdZlVYYs+L5+0d89cF9PjifcTpdcProIbOLc2aTESqQsJ5hihKdxmy1E2LpqY3m0aMzRqMJYRRSFQXZYkpVl0gd0Or16Q62qIREKUXuatbrDKwD4yjynFgpgjDE1AXSG44OHvA7X3vAnS1NICoWheR0WXO+chTrFWW2Zl6BrzM6cUgSRszymotFzeWioCgrlMrJ85w4SllMF1xcjknbHZybYsoKayxSC27dPAAleMdV/CyW/IsXDviXLwxJpScJBIlXXK4sKxQPR2ukh53tLqNlxTSv6CYJ3TSiFYC1hjAU9NIIa5tXO6s0y9IzWeacjWb0+m3iKMJ4sB6E9XgpULIJc1dVRacdsNuPSCOuXVNhsrY8OVuA0LTTkNvP3OXkyRXnZ3OEUGRZThxrSmsQMkEpgdACgoS9B7cY3NjiuXsHtNOYZWHwRhBKgZKSNAoZ9NpoPFEUIEXeQMOz6ZbY6DOmDb82/Nrw66Pqn9Tt9U9xNP04z/dxn+tjfU3e0wk828OQfrvLzt4WP3nnEa/+2fuMHr5HFElqV1PORxgn6OzuEjTVhkzWhr/8/uus1hmdXsBqPKVYzRBKooMYLyXvvPeQG0fb3Ll5xHhRMJ8tKbKCPC/wDoSQaB1QlyVCQNJOMbZmNF3gO23O1o5Rrnh8OuX8yTlKCZaVI5I1+702yU5KGAnSWNB3gpVsToPWeGxZsxhNqBYr+lGLdZ6xni+oywolFY8Wa1wQoCNNkigOOhHfeWZAGjS59lg2bbNZDllh2e1GJO2A7UEbHRvaoSSUjkA62sqztpLaeyLR+GPUUrDOLeeTFbkVqMKxyCq6kcYjQNKARgqsgzAKaYeabguccRjrqb1EOsegE3N8PmO58GxvJfz+H/4OP/nBW2RVU9yXVwWlaSOFopVEbG0NKGtPKC1bN4YksaS2hrfeecjZ8Qm39rZ57vnnSRNNv5sSKEkga0Kt0VIC7rqo9KMvqY1+89rwa8OvDb/Y8ItPsObni6LGr0pgTM1Bv83OIMa6nG7gOHn1+5y8+j0oV5g4wnuHK1YYFGW2YJXlrKzgzUfn/OT190BqtA6oigqJJ211gYB8VXDy5Ix1IRgtDWdXC7J1AR7KqkKGAa1ul6jdRsYx1ksup0t+/Np7fOMrd8hW8PBywdnMMDmfUuYl3X6bQMGNfpcXD4bs9jROwix3TFc1iyJhVcHVLOP45Ir1comrS6p8RTafY4uCWAcEkcK7iihuEbZTwkhSCUflAGTjvQFstzUyFhjfQcvGt6OXCAIVEEtPrEBJQRgETfFfYQm1pHSCi2nOu4/GjJYFXilE4JmvC4ZtjfUR4fXAodq4poNBeHAGLQJUAKvS4pRkux/Q6wdoCa+/d8bFVUUchnz1my/wwaMLStOYfc2Xa1btlEgL2nGEq9cNYLVHas1ynXN1es5f/ef/H28EkP+bf8PXvvk1WqkkCDTCVkRB0LSKwhemW+LLPND0i/p9b/i14deGX7+aNmmvX5b/sHCw+Xs7DglUs1jOHr3PH/8P/z12eYWnBpUShhGlL3FeYk3FWw+PidoJ751MWJaGtNchbXco8hJUhBIJzhqMMZRFzWSWk7kxWe7Y3d3H1Y6iKEApom6HuNUhlpIir8jWS7a272JVi3fPxjy9mjMdZ1RZft0VELE/7PDCUZ8Hg5CuqpAK6lRRDgLWRjIv4WLZYtBrU5ZrloscHcTkxiC8wjuLVxIdh+ze2Kfd66Blxd2jIfo6nG594yMSCc9OJNADSWlhkVvubKegJApIlcd6war0OO+IlCfUgtnK8t7xiJPzOSrQ6CSgqAyyl6ADTXltKy+VQCkQ3qO1whhLWTl2OworAhalxzhPaR1RHLC9NWQynvHo+Jy7dw64ffeAy8slxkIQKOrr9o68Lul2YrqtEOmbQYRRqLh7dMjrSrA6e8j3/sN/j8nGfOdf/B5hv4cQEolFXIeM/ecYH+KXYt5N8eOXdwP0hdOGXxt+bfj1K2uz+fkbLaK/dCIUNAveG2zt+B/+3/8dq+klAtMAxjustY1rqHfkqyU/+unbuLjNIjcEacz+7hAlAk5OTwjTHs6A9yuCANrtDiKMmeYVNRIVRhR1RdhK6Q4H7Nw4RAYRQkicqRkMAnYHKbP5krNJxnheML2a0mm12NnfpttNGLRTEi3xVAgBCoGWjkQaOlrSDzXDNGDQ1gzDZ5lXMM0cF6MlF0+vKLKCOA2RkSbppCSJ5uZWj+cPO7SkB+9xSLyAQAki4dGRZ20soRc4obE4pPTgJZWB0kKiHN1EYoGsqLmaLDHWo5XD1BW1s9Q2JggV4DGmcU2NA4l1jkBrjFWsc0cWeJQWGGOZ14LKK4JYsd1vsZpnTBYzHh9PGPbb9HstyqIijgK0gLKskQjacYC1FUGokV5QSknY7XLvhed49fQ1Zsdv893/cU5lLP/iX/0B/XaA8AL5ITw+n9zY6AupDb82/Nrw6+PoU+/2+jitnZ+2y+rf/Jj/pT89zcQZh8RfV8dbjh+9zw++/5coqRBSYV2FUpKqqPDOI6TA1gWLxYrRLEMFAYe3bnD75hFPj89p9XvsbO0znSyYXDwhEI6tvT2yuoYgpjYFy/mK+WJFkkbs3tinu90nKyu8F/S6CS89c0S3FTFZL8hrixQBgdbEcUC33RTDeed//v0YLxBOoBV4BFpYWsqihSRuaXbuDZk5xdnaE8cB3tYkSYso0jhniFsJ7XbIVirxxiClQniaPPZ1u0AgPC0NWjU29db6ppVWCWoEC+cROPqJoh0IMtvs1IXSVOUaW3hUFOOlYh4rioMuaShAiuaUQgMpLR1SCRYV+KUjjhWVlWSFwSqBMZ4srwiCgDCImS0yqqrEO8ew1yWgMSHLC0OcJBjrWFYlxkWkYQQ6winNtKgQSRvmc4rxCX/1p/+Fbq/Ld77zDerWh2vEgVe/0YPT32h1/idWL26iPht+bfi14devU58Vfn3JIz/NYvAIhG/+7oRE08w/EVJijOWP/+ufUxiPUBpTGJQWeOdwdQneI6RGSokW4OuK3laPdnyX7a0dHh6f8PJXX+T+vWf4qx+9znIxJ1DgtCZMYqxTKCnJi4J2p4sXHqRAR5pYS6qiJgk1vaRNVlry2jXhbW8IE02nF5NGivF8xkQ7/H6KEr6Bn3eUFiovCJQiUh4tIJAQ4Ym8JXSG3V5C8uCIQGsiDWGoCST025JOIJDWUF77azQzdEAjUK5ZvJGUBNrjpWsMza4dZiWGbgS9MEB5yJ3HXbusFtkaKksceVQa4F2MsR4V6mtbVIe1zZTlSEHmLLXxTKxHlK4ZFlg7ZtM5s2XNbLLCliXL+Rw81EqTXc25CCSHtw4pvaAygrCCOlHUxZrtYYD1NZX1VOs1UdqmtX2bGkuxuKAcPeXJO+9w5+5t9pMWUgYIIfFCIn5NzaJ/O8y70Ua/0IZfG35t+PVx9SXf/MDf3gILwIsmPFpXjiIv+f73foZWEXk5xbqSWLYxZYmzBUprpI4QMkQqwaCfcOtwyGpZUNWWVhrzzVcecP/2IcZUXByfoUPJ/u3bRK02o6s563WB0gFCa6RSTGcr0mGf3nBIJlbsbQ1AaubLGVEQEakCm2h2hzvcO9xtRu7JPtPVmg/OJvRu9UlaAuUdtYNl3RRBtsOAQEksoplWbByhgp1eTCc2BNC0ZwpBKCx7saAfSbJSk9WeKGxGFwceQtEApDlpCpAOLwRGCIyHvLB4AZ0oIBLXE4+FYFXUTMdL8nlJANSscDJgtQoZzQoC6dlKFVHUHM9mS8PpOEPFaeMGawWVqZivM6pKMbpasFouWU/nrC6vuDx+jDQ1WMtyMcGaksMXX+b5b/4eRWWJw5CzcsXWsEOSpihvcErR6Xd55uWXsHXFqtWifqKxqyvefe0n7OzvcH/4Clb0wFmEkn/HOtpoo9+ENvza8GvDr4+jX+tg00+z7fPj7SoFzVicD+edyCYn6jyllVzMSj545xGnZ5cYU1NXBToMsA5sXQMOqQOi1oC0M6A/7HG4v00rjqhrQW4ynn32Ljf2emx3NdvDHq3BkKgVEXS6jGZLxpM5HomXAhmEOAdJ0sYZRyAcnVTSbQtakadrNDERpgoZDIe0FQxbMYUxoANWlePdkzGp9Gzd2yIJIAkktWhu/knufj7fxQmFVJJ23ISYW1KgpWSZN4VxGkMiYiIBNpTklSENFKEQqCayCzSGXtI1JzUvwHtBaTzrsiaKQwLhkbYZtFgDa+MQUqOkBldh6praw3iU8766IJvF7L94QCts3otOO2BgYs5XNWfTOcZqkiRiMam5fPKE+fkx07PHrEYXlJNLstk5zmYIFVD7gLg9ZDmdQl1z9vgJSRRjypxq3UUCRTuh1Wsjg4DOzg5HL7xMfXgL7z2Tt8aU8zGv/eCv+Or9IeaVw+v5QtczlH55JW3MMz4X2vBrw68Nvzb8gi975OeXwHGdEObDVVE7xWuPLviTP/1zCpPhyhLpJVoF1NaC90ilIUhIujt0BkPu3b/D1vaQ6SLnYjIjTGKiQOK9ochrXnv9LayzRGmC0po8LwiikChsoYOgcRetbJP7xXLYi+mkKZ3IM4gcUdBiaRWp6nLQixhowFsqHbOs1jiTUeYlWSVZV5KulgTeEitBLULWzrEsHNI7Oi0NeEIJkQAZaPLSYG3FVi+lrZsWTOsEGk/mLblTSN10TWgpMEBpPSGea1d6Ste0ciKagj8p7DWwwDgHElqdhHKVUWUW4zzWOFRdsT2IeenZXQ76iigAJzyp8iSDiCSFwmpefeOE0ck5YVVz/NpfcfXwh/j1GFtlOFuhlEBFKWlvn2h4k8M7zzG8dYvDwx1OT55wefqUXqdPVTrmqwKvI4ys8RKMh6jTJtIhSX+HsNWlWs+YXxzz6o9+TPGvv04Q+WapbLTRb1obfm34teHXx9aXe/MDDUDEh+WCNPAQMF8VvP7mQ95/7wOUBIsnjFpI6fB1gVACIxSd3h5BOiRMEx48exfnLFlZIZQCb0migG6nz9vvnfDjH/0MVER6c4dWKEmjDhO3oLKGqi6pa0NVG4p8ydEzd/jKjT5tbZBKEDiBqQV1kaO9YRgmbAUO6xyVtNwfJpCntG5tg4PzZUGoNN1IUHnPujbN8EAhqcqaIJC0AkeqJUIKHOC8ottNCZXA1gYjFEqCEqB143dRAMYYZKxxQpAbi1RN6Lj0gpVpbOOjICCiWWBCNK9urARb3YS9/S5aSqajJet1hZKCvZ0WLz+zw7P7IQPVvCeFE6ytZ2U8o5Xj6ckVq7MTjn/y19jJOfnlQ+rlCVI4nEpIhke0B7u0tm4wvHWf7u4eN+/eZLjdJYo03/rOV/mPf/SfyYuSIDeEuSFqeerZiiBUyCAgjEKMMbT6febdbcr1iHo547Uf/ZjpZEpnv/+LRfMb0id5SvvwsT5r+fiNfkVt+LXh14ZfH4tfm83PL8s3IVUvJbP5gkdvv41ZrnE1KN3CCajrFd4ZpA5JWgPS7i5B3OHw5g0Gwy6rrEBHmhRJoARbnRaLacaffvcHzKYz+p2Ucn7Fze1vgFS0Q800K8iWa3q9HsY7AlWxN0jZiR19BVYoVqWjMBUeaMcRSoHWHu1Ae8etJGTv1hDCgMt1yfm8wM9rjrZSciuZFo6iBoRAaoWU0A4laSAxDgpH0/Ja1SxWgnaoCQOBFo1rvXPNySdWCoRiua7pt0OkkqAkRsC69sxyQ20F7VASCdBCIn1zWouFpBtItvopcRKyc2OLk+NLkijiK/e3OeyH9KUn0U2HR157FpXk7bM1P3n9mMfvPOL0te8z+eCnmMUlAYq0u8/g5jP0D++zfesWaW/A2no621uEWrC912d7K0YKx3ZvyG9/7Xn+4nuvEcUpi+mMqshohyFaS3rbQ9I0prQl3a0tRr1t5JXC5QX5akme5cCAz6tHxkZfcG34teHXhl+/sj51h+ePsyP7tVrMi2YpKO8wQuBF0wmxWizJFhlxPKQIW/S395lfnpBNFmgd4WVC0t9FpD32b97k5ZdeIAk0pB0m2QIlwRjLshJ87y//ip/+9GeIfEWlLIFyHG2FBEJwe3uHh6Mlq0VG2h4yWxWslmPKdUaCI/QWKyStEG4ITT+SWDyxBiUEUkqks4SUJImgEA6t4GKxRvqUQUdzVTgWuWmAoD2FExTGUVpJJPm55VWoFRpHKTxeSWrnqaxA0TxXrASJ8gglOV7UqFCTSkluYWHgYg3r0rHdDogUhBKEF3gkwjvwnqIomS2W7A76HO50OOgHdCPFg90WRx1BJ7CEsrGTF0IQCIhCzXQ05fEPv8/q8fchnxOoiPb+Mxy++C327j1Hd3eHrb0+w07AuigoRYA1hnYk2W2FaGnxHn7v917m4QePWa/W5OMKEzhWQNrpYH3Fvft3ODo64M7eHpRrfnb2PuvyCSqMyXJAica+/xNdoX+/Pu2IzJc14rPh14ZfG359+vos8+vLHfm5DheLn7+A12WDKqC0gu7uDeKehzSk3emymIxwCJSKCdM+Ourz4NnnuHPnkPt3DwmCiIvpiuPHT8nWa5zzpHHKa2++x3oxo1pNwTvqsoKyYLuXECYSbwPSZ7cRSZ/XHl/Sb29xuNUjDBQITyQkWngi5YktjLMSb2km+EqFwyGFb5w7vcNbS0s4OmnEPCu5mGVIqdnvxMShRNdQ1TW59YTXLqReCCIJ/UgTaUeoLIH3aK+ItUQpcV0k6CmNZ1RYzMoSKLiY15xOS0rn2e0G3OgHtDSEOJRvculrp1jUYJwkFoJBINiJBMPDLv0EhlrQDSCQEkfTceGEJ1CCnW7ErYM93nQVriwJ4gGdwwdsPfcNeneeRQ/7qE5Cr59yayfF+TbjtaGqLMN2QDsUhFpjr+scvv2dV/ij/8+fIK1mOOzihCSOUpxzOGfQgSbLMhASpWK88HgkZ2cjXvmtG1+awYBCiC9lIeTnRht+bfi14dffq3+MXV/uzQ/XdYLXtmAgEd5iXEhBRLi1RzuMibst0jDm/R80U4yFUjgvGPR2aMUxL33lPlJJTs6n/Pi193l6esp8dIVC4I1jdHqCyVdUxYq4M8RUhjKraO/2EVQMI9i/tcvIKM4mIbd29nlhLybyZXMyam4npPBEKiLUAc7bZtCfl1ia+THCe5w1bPVavKRblN6QWUs7Cthpxxy0xPVjCK5qgyMABViQHqSEWDV26pGGENACQtW8ULUTFK7Ji1c+4q3TirPRmMuLFYvS0x32MSbl9jBGJAK8wynJ0sJ7C8MHo4qLeclg0KXfjYiVpxVCPxZ0FMQSEALrofae2oFxnnVmOX56ytJIOne+zuDwJrv3X0QPtkn7PZI0JIoEoTAkAbTikCRU1LWjFytagUBrqAzUCl588R6PHp8zupjTbg8J45QgCUk7ATqKOZ/M+OCd93ny7lvU+ZJANr4Y48mk6ahB/Ly2YqONfpPa8IsNvzb8+lj61B2eP8nP+SiP8VEe3+OvjZ/4ubHWxXxNd3ebw90he/t7vPX6O5RVQRhEYA1KS4QS3L53k063y59/9wc8Oh5xPpmiVcDscoTNMxQCl60xRdE8mVCoICUznhyJFiFWaKa55XS6ZDWecHBvl3ZgkEJgnW6s3gUomuF4WgdIYTC2xvqQwvnGvRVHbR1eOIzzFGVJHGr2ttr0I0uiCvCKwutm7LDTaAFagXUWg6T2Taus85CZpm3URU242fnmRGM8XI3W/Nfvvc3Z08dU2YqjZ1/E9gaMl4YPLnJSmbDb1gTArHK8c7Hm+6+fMZmvuXNzh5sHHYQWdCNPXzti4dBCYFFIHM4I8hqWtWC8rOhtD/nD//Z/TVYYfJTQ3dkijDWtJCAKA5SviQOQ3hPgGcQSG0AgHfLn763HWYdUkt/9/W/z+PE5J6dzwrhNEGp2D/p0uwlnp5cs5jNW43NMsUR6R56tOTk9BddA8ZM8Pv060yQf9XG+DGmxDb82/Nrw6+Prs8yvf0hf+sgPAKKxNW+WmGKZW6Ik4Zm7bV5+5ia1U3zvTy6AZsPsTY0Sgle++VVuP7jLd//ix/zoL3/GYrHCKRgMtzHrJTZbNoPyfI2tS3QUE7e69HZ2KVTIeQ5FnvP+oytOLseMZwXaGaqX7rLqtjhZWK6uluwPQw6GEaF01F7y5GTEjZ0O3a7COkleWpwU4AXOK6xtDLqGSUAvCoikQAmL857KCWrn0GGEUgGu9uhANKFR3wzx00ogpcB4h/OC2ntCIRtnVwHUjp2dLnfv3+LJm28ilGBnq8Phbszhboc0gHHpyJxjGCkqKUHFjZPpouRqVvHB2ZrkMOV2WxFKjxYede1Wa5AUHjLjKOqK7UHI//xfvoCzntNxQVnVtLspUkus81gncVaTho7aeYz1tCKJ0I07mby2MtNKgrMYY1GB5Pb9I3TaYjRZEsURXkmq2hIHEVQ1NptTlyuSQOC9wfqmS0J4fk3+qJ+uvgwbmy+FNvza8GvDr4+szeaH60y5cAincUJR1JYb+zvsbfU52u/yX3/0AePJAiUlpQEZdDi49wJ3n3+R7373+7z7xtvMr64oy4re9g7Fao0p1th8hgwDalMjg4C41WHvxg3uPvsMNkh5PCrwDmodkxWObF3TCSXj8ZLaef7yJ4/4wY/f5vZhl//23/0zHtzoMq88bzy8REjFdreHByonyAw4JM41N2AvFgwigfaOZVmhtSTQMWsDWW2Z5obcCnRLEShAKqQXhNoTKIgUqCjAIa79MhqX0/V13rvXldy+v8Nwb4fcewY7Xe4fpNzZbVpELVAax6Iy1B6K2tLutXBKsigtbz8+52Z3H73TQQl53U7aFPVlDhalRwnHbgs6kSaRjlrArX4KzmOFYG1gWsCqdDgr0UpSWkdeO9JQ0rquhrzODKAEtJOAyjm89JTGcefGgChQ5FaRlzVlUVIs1/jaQl3gbIkREh3FJO021jcTkjfa6LOiDb/Y8GvDr4+sf5LD89+18/p8OaTCh4nPD4sGrQetFLu9hJv9CFPkPD2fIHVMq93FFSuSwQ4Hd5/nf/rP/5Xzp6dNWDifIqRGICnyHFuX1GXTZuqVJggjvBBs7W7R6vW4GC2YTxZEoeToxi5/8Dsvs1is6bZC7h90kUrxjVceEKQpV9MVbzweQ6CZZpanoyV3791iVXmkt2Q1LI2ncs2kZiElLRVSKxgXBZOiZhindCPPujIUNXgVcjZfg9WoXkwkBcZ7TO1JtELTAMA4cLbJDy9rmKwbW3gRepSCqDtgq5tw79Y+B/2InoRUgFBQBBKEJK8c3chytNcn73dYl45+R7PdTdGuubu98FgEtYdl5VjnNVvtgL22JvIQIiiVoNbNe7auGyispSdWHidBKIlAUVpDWdb0ogCtGxM455tTb6QhjWRjClZXuMoybCU8HS2ZrzO886xHU64uL1gtZs0UbEJQmqTd5tpZ7iOvv03h8GdDG35t+LXh10dff19Efn2kzc8XsQbAAx6FQOKEB+cYpgFdFO045KdPFmRFzUvP3ubPz4852LmJKzPOHj1kMpsjvcNlC4p8iUy6BFGIjFLWsy7KFNhigfAeaw1BEJH0B7z/9Ix8vmZ6ecHu7oDtdotbtwYMbsSkSqBUY9w1OGpxe+s2WS3IjOf7bzzm1bePWUyvuHv3gKR1iLQ108KztgrrPWEAcSBZlI7aWkaLHKECuolnXtWMVoZBqtlNFOu1x0rJuoZSOCorqGtIA4fQCq0cS2Op0dQGRplnmllCPIHRjCYFPgm5ef8G3XZIpGnKLoVHImhLCKRHhZJb2xGVMWQlBFHEdkuwmyqMBCuarooSzdIIRpkh1IJhLOlI0HiU94Te43RjRmY8xLUnkY7cWiwC7y1KaZyXLEtLp3IMU4nDUbnGJ6Swirz2FAYK41iuK2ZXYwaDHrWTjEZrzh8+Yj06hTBClQqCkN27X6G/dYB1HiWbMPQ/urau2103+mxow68Nvzb82vDrQ23SXqJpD+X6dykEkZbEOqCoSlZlwc0buwjruPfiiwzabX74p/+Rydklznm8NZh8jXWOJEwA17QY6hgjm4WshAIhSdMek6s50ydX+KIgX80JxD1mg22m4wmHt7eIlEPgEN6iJaRthfdQEmCevcPP3njCdFbyVz/9gKejAi0d/UGPMEpx3jPop5iqJupFBMJzc9gm0AFIwTwrgcbavfZNkaFUIbWFMJII71GBoBaCZe0xCC6WhtGqwlhYG0FhmpvZ1QVPjs85PNjnaGeLWDeTpT3NgEBkM0PH++bkEkrPza2EPDMkoaDd1hTWcZl56lgRI1g6wcm8RHrP0SCiqzyht0jRnFY+tPLXQCAkWgqkUshQUWclZVGQpCnCOUoF07w5RQaBxHuo8WS1Z5ZVlBZq0xRYPjq7oJ3lbO/08VVFmrS498JvMW4HPPnxGKljnn3pFXYOD5uvQ/zqgwG/6ADZ6DesDb82/Nrw62Nps/nBfzgdp3FIRSBEkzfOyopuOyJpd5hMFjzz3DOsRpcsRieY9QgpBM5asBYZpkgJVVFSeQd4kAIvBdY7oqgF1vPorXexzYVIKRlfjsmPMoR1SN8Ut+EtwjsUjbW6E4D3HA1j/vD3v81f/PhdhFZs7+6jpaHfjpnO1jgVkBc1KlRktcUpwTAOSUVjgNZNAgYpICSjZcXlJGOydOwP2nS9wHtPEkgqJVhnFXEQIFTEsiopq5qsavLROEG+Lnh6OubGzg5lXVMYifMK7yXWC5yFEliUsCgstbcM0xAdS0IJcQJV7blYGJ6MDLWxzAtDYQ3fvtNjEAkiXAMgQQMkQLjrllgvKKxgujaUVhAqRRBFJJFGCvDGsq499drSjpvW19pLcuuY5Zaitri6ZjbPKWtHfjVhOZsyu5jRH2yjd4YYW8Lbr9Pud7j3zLPoKGyWibcI1Je+VXSjz4I2/Nrwa8Ovj6Pf2Obn03RY/aiPKa5NoDwShMB7B66ilaR0ywqDgF6L2of86Y++h1nPELZCCJppwEoSxCkqTKlrizWGQHqMM03bo/U4W1Os5/iyRgcJri7QcYv1eo0OYKvfIpRNkZyj2Z1/eJN4FWCtQYuao70OLzx/hMdzY6+DtBXDYZv3rSE3kl4rJZWWxWzOyEPR7bATS9LQ0w0FsbRkXuKsRUSNmdY0WxBHAuktR9ttWjagzB37XYiVoB0q+knjDfJ0tGC+qskKQ7EqeeP4R5TFnKsb22Q3d+inmk6iCbSg8vD4Ksdbx83dlAhoBQKlPNJ7klBRtBVj45lVNXltuLXTph2J61Psh2H9Dz1MPA5LhWJmFBe5Z7SuiaRg0AoJ0hgpGyv7wjZDC5dVSW0DWqFEBopFXnM+WVMbj69Lnj48YX55RbleUmQFe4c3STox3X4Hb+7R3r3Jt7/9NfZvHOB83ZyCfnHY/khrTgjxK9d8fFqnrS9a2uc3pQ2/Nvza8OsfWpOffX59pM3PLzu+fnEg6nHe4xHoICIIQsqiCa8K71He4XC00xaPnx7z8M3XkN7jRYQXDrwFFRKkXXTSuG3aeo12BmsqpPBYa8lWK1RZEUQlxIaqyOkkbe7cvc/+wS5pK8V78+HdAgIcTbgZ63Gued2TULCz1aauaxJtCUKNBLqtiMRYjgaanpZIoblcVkxWOfgWSVlwazsm0hLtHYM0IF4ZjHXkRc0sp7HFL9Z0uyEtDcME2incHGgC6QkCSTfp8WRckWczVF1x+uZrjD94h51bRzx+4Rn6+3skaUo7iVBKsMwqdnod9mqJDwyBahpyvRN4D4HwBNTs9ANcS7EdQ6w816MKAX7hceE8BYrzHH76dM57oxKlAu5st2lHEiHBWLDXtR06DKhKmK4rjAuQtSevPFejOZOrMaooePrue9TLOfliSWf7gJ29PaI0RAeeW/duE/2bf8e/+OZLxK0I5ab8fQWDf5e+qOHiz6s2/Nrwa8OvDb8+1Jc+7eUBL5pTkwpidBhincfbmro2CBmig4TzywXvPXxIUZQEYYrSEcbkmLpABjFh0iWMWwgZgioxlcN7cHiMcyRpBwngPabKqU1G2mkhVMTx00sWLxzSCTXau8aG/Tr07PAY71gZWNWW2niSKGoK1qTCa8V0uabTioilp6dr2kHT0dDeimjFnkfjNaV23BYpGofC0o4DNAbhDQ0oFUIHOK1ZrUva/QQlHC0tSVvNTZB7iCKJ1JqidlS1IXQlV2/+NZPjDvPJ17jz1e8QD/cI4hDnDd12Bx0YLhcZB+0YqSVCNEZjawtPl54PrjJaoWark1A7j/eqGURI09XQVBF4rIerWvLuKOfN0wXjzLHXU2jVDDq0WGrbeIFYqalrh5CKWVkyL3JakaYoBa6smZ2cUV0+5eKd18BYku4Od+/fpTvsEqUh0hq2hm22+79Ff7tLgEXl1zD4gkNho8+PNvza8GvDr4+nT2zz88m3cH785/xVr/vwkAJQljXLasWw3yNSiswYprkj9xGTyYLpOqPVam72qLVFGMWU2RyPQEUpKkyQOiaIUnyVUwNR0iJbNrlxpSVlXhLJEFMVKCWZzca8/rNXuTzvs9sP+P1vf4WjXkSEaYrjhMcJR+YkKwNr4ymMA6GQorFOny0LptMpd3Z69HoxsW5CztJbIlFx2I2pfUpdV2gBwhqsEASBotOOUdMSa2qsrRFKYlRjtnVzq892G2LtwQsmheDRtOJiXvFkVLKqLEHSJooitBtjF1dcvG7JZobtZ15i/8FdZKCY2ZxlURGrmJeOYpBgrWBaet6ZVPzoeEVRw8s3Qnph45iqRGPlboRA+KZ91DioLJyuHJfLiiBO2U003VghFQ1krGu6JoTEeU9Z1lg0uQm4vLoi0eCcwJUVi7OnXLz+ferZKWl3D/Q+IokQWiGlpp2kON8UkI4XKw77CXGg/sEuiV9X6HejT14bfm34teHXl4tfn3jk58MX8PPzwjWOl8ZYHk/G1EJz0ApZOc3rpwvW9QrhLYPBgFYcEkQd8CnJoIPTGqs0caeHiNr0dg9JkxbH0wuMM42VPJIw1FTFCuc8rha42iDDGLeeUxQl56sx3/vrlN29A3ov7hOGTZ64ch+enQSJBBlq8A6lFEZqSuu4mOXMl4b7u4J20HQUCA9aNa+/9obdRLESGouiEAGVF6wKS1lUCOdxxmJqQxAGWCMIE8UgEQjvmK5hWTveHxkezQrq2pPlFiU8YaibVIJXKO9IwohOb0DS7SGEAgMVNUkUsNPt0FOCUMACz6NZxWunCxbLjLu7PZ7fC9mOPFIIpHDN5GYLXjbh5cpCaQWF9Qw7Cd22QEhJpKEVCmLVfLxEIKTA43BSMV8ZpvOc6dxwVeZoW/H41Z8ye/QmZvYEbIWUGh2nlN6zzGtqB1ILitLRCgR5EDLPSnppCM4j1Mdb2//QD7tfzqd/fu6dL54+f+/Bhl8bfm349XH0pU97XVcAAJ5HT05AxWgxYJQ73nx0CWge3NwlDkPmiyU+DBES9GAbLQSRCoiSFj5MuXHnLnmWYUyFcw5UgJABzuZ4DwqHqZYY6/A2p6xWBEGLWiWcPh5wejamevYAHzZfV2mhdppYKVrKEXtHGEFuK4gE01KSrdfMp2OkHyCFpLKCy8WaTmjotxtjMic0a+uwmUNLSWHgYlFyMVtT1R5rHHVlkFLgrML4iIs1nEwsT6+WlCLkclWyqC04gS8rlLNILE44rAOp2wTtHQYHN2gN+jgBcZQQJJqDQcSD3YRu6HHAeF1TVAUPdls8s9NmrxMyjCDWYLygsM2MnrVxYC2JlkRa4LyjF1oGiSJUilA1gwsDGtv6uVCsi4rZuqREU1nJOq+Yz2csFxk+ryku3ufpT/8CM3mEcCtU0CLq9hns38ChKKsaoWC+rKGwrKUD0cUXJQdJm7p2BPK6qOETvsc/KWj88uP8KtGFf6iQcaPPtjb82vBrw6+Px68v/eYHAO8RQnJxeUWQDpA6ZpR7Lq6mbHc79Dsp3lhOTy+wzhNHmsHuNt4bXKAwtSNut0naCZdX54gwJFQDlHO0uiXZLEd4izM1QjY5+jCKybIlrsgIwpR6NWc0mjDNLK1QIpxhVQsqB1Z7IulQwhFLCGXjXlpoRaQVpq4pq5pVlmG8oqwqWpGmRmGsYl44nk4ycgq8EBgHWWVZV4KirLGmKVSsS0Pu4cwa5usC7yXr2tEZRs30wKJGoEEqlJQIW1OUS7wMiboHhL1DrEooioJYSnwi6Oz0GfYlaSQat9TSsc4dR8M2vVRiHfjaYaqaHI2TkryGrIa8tiQSOmHT6omHnpakoSSSjTusEk0g13hIlEISYBw8XdaM5hWj0YLFPKOYryhHI05e/WuWZ+8RuhXOOFQYE6Y9Wp0h3kIoJYe7O7RaIWePLnj0/juUeZ/D7RazLMQ4/XO/jmbpfPY2DZ+kc/FGnwNt+LXh14ZfH1lf6s2P4Bddf1EUIJzn+OSc9mCHs/EaV5fYSuKBv/7hqzx6fE6S9oikIwol+wd75IsW0/maKG0TJyHdXsrB7/4OJ6fnLEdj1lV23R1gETT5YqXbCBmgZYE1a6raMLt6wk9/9CO2dwb8zm+/QJpo8tJgfeMxsdNq2lhtURMFzcyaSEA/DVn2+0gVIIQkCRSd7Q5KeYxXTNYVV7lgaRTns5waiURgnQcrGJ2NWExnBFGAMQYhNUErBSHodDoknYRWIpE6YrGu8AjQIc7XmCwjm5wTtvsMjp4j2jmiMpZqMicUijpoTo2dtEdRWzIj8UKSphFKC0ztWVaWykpwEBlHFCqyEtalQQgIIk2gIRCNkVkqmw4LjUWKZjqxFwLlm/bT7VSRi4izHBbZiqvxgnw8YfzwPeaP3yI7fxftC8q6QMsQHabEvSG9nV3SbovtXodAgilLLs7PefTeQ8anCl5+wHYC94aSXhL/JpftR9ZnEXAb/dO14deGXxt+fXx9qTc/8KErqmwm8pqKyXLExeUFYTJAeYcSij/73l/z2mvvUFeercEQqOj1ugyGO7z77iMOto7wwhEKwz//1kvYKufo1hE/+qsfsTj9AOs8EglSooMWKuwjgCA0GO+RUUCerTl+fMx/+i9/waq03H/2DkhPEiiGnYBeK25uSG9oScBDJCwHgzZJnNCOBO1EIxHI666BtYFxVnE2N1zMKyaLAiEjXG0p8hyqmouHH3D55AO8yynrilZvh8HBbaJOn1iFdLst0jAgqyxJkhAIR5ZXLMuS8fk51XJGZ/sIH/eJugOCOGa9XGIqgzYluqrpt2J0KCm8J1QC5w2TlWC8LPnx24/pdHp85d4BO1pCaaiMRytJrFVzIztLIKAdKpoqhKaoUAiB+3ngXwBNK/M6t5xeLrg4n7EejZm//xZnP/sLivEHKLNGSIvANuMOdMzw6CY7tw7oJJpBr4WQkrzIMFWGLXIux1POBi3uHG6RW4FF8Hd5pH4Wc92bjc8XWxt+bfi14dfH05d+8wNNcZmWkq1um3cfvcfycJ/nbz3gbS949PAJp2enuNoRi5BAebo7e+zu7JB2+ug0JU467A9T7mwlfO3+NtPlnN3tAR+83eJ9b/FCoaIAK2Oi9g4y7FBmOVHaIo3uEXeHrMdnxGGL+STjhz95j6lR7Oxvc7gzRJWSea5wpgIHvVQjnSFUgu2WJtSSri6JhcCiEEIRCIE3glpGFAgqW2ErQ12UzKdTJleXuGzJ4uQDRo/folpfIoRl0dmhXv0Wnd07uConaoWMpyllXXNvmLDfD7hYlPx0ssBaASJCBB1k3KY16CEEFHkBgSbotHAyZLyoaGlNKgVhIJBCsSoMk8xRyJRqVZAXBWEnRdCEhAOhSDSETZQafZ0fl1zbxV+DQniP99cu/0gqCxfTguPTCZfHJ1z+7IcsPniNYvYEZ9ZI7/DGNAWF2hNECe3BgKgVsb/dphsHFKVB+YDdnQHHgabIC6ajGWeXE9bPDPBC4K9xtdFGv1lt+LXh14ZfH0cfa/Pzj1V9f57kvb/2PfDcubHP//Rfvs/VxZid8QxXV5w9eYSxHi0DokjSaileeeVFkk6HybIkanfoJopvfuUm97YiBmFN2ovI6pJivW6s44OE1tYuVe1pbx3R3r/NdDqlE0kO9nfYOrrHD7/3Zwz6PfaPbrC1v4tqdcmt4mqRM5nW2LpD4Ep2OwrjSpQArQNa1+2MsRDUlcEICAOJRzBdlRyPS0YLw3g0Z3oxZjWds5yNmJ8/ppqfk8/OqJfnuHKBVJBXC86Xc+b992nt3qBaTxiNH3Dz9j7PPNPhmR3NeU9zdpzS6vdpHTxH0B/QGvTZ3tnCCk/UbiHDkDAIqWrHxaJG+4JukBLqkAqYZB6hY+4e7VMUK1SgmiJDKQlFA4pQegIBsVKEorGG9wKsEGh8E/N34jr878mMY1EpMisp1xkX773H4vQMREBr7z4mX6DLjCJfABVKSpACe70OOmlAJxB0k5jFCm7c2OPiwX2sqbBO8v67x7x/EPHyzReakDXwN6sG3fW/Pxv3wCbq83drw68Nvzb82vDrE4v8fJ6dU70QeGfYHnTJV2sevvuItUs4efwBQtRsb+/hvKTdbbN/dEi332FWWGZZRZy22N+KONxK6EaWwDdTg01tuBrN0UmPncE+Pm4jnCUZHnDjwQMGywnPH23x7a+/yPEsZzF/hn/1e7/N83d38VLy/bcueP3RBcs4QCvHQT/k/o0Bw6gmlBU4SYAn8AaHI1CC2jqcAuthXno+uFjw+GLFelkxuxxzcXxCPp+wvDohv3qIza4wZo03JUIESN0lige0Wz3W2ZTV2yfMnj5k7yv/jF779zF+h1BDEIJMQvpHh1h+G6MVw6Mj4n4XA4hWjbONyZnyjm4cs93yCOPIS8u6FMyyDBUGdFsxoYqpakdegQ6gFUAcQqQEyjeGZ857SgTGK3CeWDlCGlt/A+TOMq0kJwvHxbzEesVw54Bh0sI6g5cCWeSsL4/R2ZxWJ2L69CHGOuqipi5rlBTNCU0JWpGi02lzcPcuQRRiyorx5SmLVYl1zXXwy35hn511v+ne+uja8GvDrw2/Phv6dfFrk/YSvql+99DvdQi1YrlYEE0nTKYTDg/2iNKUMGlx684dtg72mBcVWeEw1tJqJWwNWmjhkMIhASUV3glqL9g5usu9B/cIel2sClkuSw53uzzz1X1eebBHv5uwfHPF11++ybee32E3MuRW8aYyjM7OiVod9g+HtNKYWHkCKRAihOu8caAcdVUiRYCXYJwjLwxvnue8f7FkvSgYHZ9y+eQxq8kVrlxg5qe47JK6aOzOlYyRskPau02ye5d0a5dWPSe7eJ/VZEY+n7BYrnjr6ZTt7g5PF4bLxZqw1+Fm6xniKGC41yNIA/LKU5mIdZ5RlBmegL6qeXYrJVFQOujH8MJRF+ctUgjKMEYJQaxBSYikpaUk+rqzo/KeksZtVliw1tJL9TU8mo6SRQlXmWNZSiwhrd4W2zchn08JdICXElfkyFaXjvS00wgZ9Lh6+gHr2Zz1fMVyWZL2Y7wzKKUQQtMfDNFKMhmPKOo1y6ImKw1Rel248BmCxkZfQm34teHXhl8fS5/I5ufzeFpqdJ33dA6JJAo1SRxSesnOzhZlkbG9t0d3a4fe1g7tbo9lXrEslnhCvBekkabbitDSNdl36akdvPnGu2itef7ZI/7t/+w7EAbMM8dqVXE0THmwH9ONSoTPOdpKuLN3n2FkCXxJLltYHMvxGFdYFlHAD19/xOKgx4ODDnu9mFQrBA4tBEp4rDF4oTDWU1hPVjlq13QkrGdzJk+fsBo/xddT6nKBr9aNBb1QSKUQMoAgQLc7+KiD1Cnt7Ziwu6Jz8xZWBFxOSq5WjsIIhISDG1vc2O5zaxDQ6yoK6xjNLaOF5fi8osgE1npS5WgrjxbNjd8V0G0rlJYUtWNlFBboxhApCGns4XMLufEYKTCi8dgwlWO2qolyiXAWoSRhoCiMYFQYakKklISBoNNLG48S54nimEJaOocHCCmxRUZ37yaL6YyqKFktllxNlySxJhAGIRSrvKC2FqckhCGHt27jdMV0UTBM2zRhYv/zoX9flnDxF02f39drw68Nvzb8+rj60kd+mr13UwCmNBze2CO7XKEDydHNG+zu7dPub+NlwOOnp6yLCoMiDGJCHRIMYoQrkEIhpMAKzfm84I23ngKwv5Xw3GGEEpLKhRSlJdWejqoJnMN5y9EwJdKaEMPKh3wwLXj/yVMmTx9Shy0wGTW3WFcWISFNAkLduJ9qbwhpJgEL4QkFWOEZtkNC6ZqBesZSZQsoZ5j8CudLhLPgQAqHrzKMsIg8JcmGYNeYCoQIGdy4xdbRTdrtDrXXjDPPfFUSxyFHN3ZQzrL2BrPyTMZLsrKmv7PNaB6gVyGmrhvHUgHGOwIFsWiG9ykp0aHCS09lHNo1dvDnRnAxy7EOoiQiiQSRFI1XhlYsjeYidyCgqAqSMCCMAyZrR1GVZEVBXZdoBXESUVQlKoA4DbE+QmtNvRZEfpcyu0tlmknWq8IwXlekkUB4y3KZMboYk7ZihltDYi0IfcbZ1YJ7e10+HFz4C3024LHRl0cbfm34teHXx9Onvvn5qG6Nv355vJTNIULCg2fv82T+Fq12QhTHhGHMfLFmOs84fnqKjhLCVougHWB8QRpKAunRSmBcM7vmz37wNqNZjgg0OoxRzpNoQ6gV7UASYj7s0QBnSHSNvrZEP15Y/uwnD/npD19ndXVOJTSt7SFKeLaGXfZ2twmiiMKUpFJivaByntJBXRX0WgmxVux0E7b6LU7PZhT5HMoZrpjibYFwNcI5vL8OfUpwQlJkS66ePMRJiVYx7e0b6M59RNwibrXJrOcvXn2EQBB1u6zzEgFcLhy2LDl5fMbZ02O+/tuvkHR7HMUp1BmrsmZeehIlmgF+QvB0vAYJvXaICAKc80zXFisC3hwVvPHoHLzgcG/Ibj+hGyo0nrw2XEwrKicYDFrUQpKtDdPjEZeTBWnaZZEXFEWF8oDWaKUJQt2cLpHESUyiHMuioLe9T2lqlrMZVX2DxdpgfIhzjtW6JF9mSO+JRYwXGhmlLFbLZm6jAPk3ekY/dF75bGhT+/NP14ZfG35t+PWb0afNry995Aeu97uiMQO7fe8O+qfvI5XCeoe1lsW85PjxOWVpiOMA6QXles3WVo9+J2Vvu4NWFucc7z465dHTMV/52suk/RhCz7rWRJGgNID0SOnRXuKcRCGRVNSEzK3mtccT3nj3gvWiZntrl1WW4cOQXjvg+Vtb9NOAdWGZ5SXDdsQ6KzFCczKaE2tN3NZNntl54jhBSViOzykXF7hqifMNuPyH7mhC4pDIqMfBg1eId+4jog6BCtGxord/gE5Tqrqm1elS5I46r3EZPFmNqCtDmXvK1Zr56IrpaMZrP32LZ19+hu39Pr2kSydRZDVoKRHA+XTNpDB0QwnOEwKFEFwWjtNVznsnK67GFmc82XrCZVuxs9UlDAMuJkuWyxrpHdaDDgOK0nE1ynnj1YcMt4bIJAApiUMNUqKEQsgmFB0FAYGURGnCAk/U6hK5GqTkvbffo9Pv0el36fV75EWJLSpya8iLNWqrRyEi1sJSlIYk/sVwgQ9nLP1iQf169dn8wbzRr0Mbfm34teHXR9eXfvMjAOEdwjeThnv9Fq12i/OzEVGSsLPT4uriiny1BiQCj8ChpOTGTp+9bkQv1AjjGa89r757yctfeZHB3h5GwmI55fGyQscp1nlWWU0nDgicQVpDO47wXuK9ZLG2jBc5Ukd0dw5ZWYvMc3xd4gvLdFFghQehiCpLEnhWlWZSWh6fj3n+wV3OMzibrDkerXnrzUdcffCI2elj6jrDY0E4HBYkSMB7iRAKbw1lkXF44w7Du89isGBy4iTBS00gJb4siKMAYyxSalwdcPn0lGyyZDUe412NMRWj46ekScRyteTZ+wf0t3qEgWVWliyN5GrpuL3T47AlSTRYC6WHyllGi4Kscmil8K6kKgyXq5rJ1Yz9w32MFUxHM9bjKeOTS9q7WywmE64+eIitCi7mZ7SGu4StDqrXAqUQyoMKqVRI0gqRyiGsR0qNDyUqiGl32jjfOMdOx1OquqJcrFnOp0ShZpktENUunTu3GFeSSQG3I/DeUUuF8F+2oPFGnwVt+LXh14ZfH08fa/Pzt8NRn/3Q8D8k8XOTKSFgq9/hqy+9wHunM4QIGI0XZHmFd+C9wZqKVMUMBx3arZjKOqaFI18tefPdYwa7ezxz9xAVaLLa4l3KaG2oXUYYxUxWhiRSTK7O6QSC527tk1DRSzWDVsBL9/a4uJyxGMN6tWA1vuDkXZgvCsaLJfdeuMvuzg6DIGBSezKvOR3NqWrBYlkxmi/44HTCaJZx/PAR86cPkbYALN47/M+L3Jr5Oo2jhsWZjOX0hPnVY+KdLTq7O6RRiqkrnHeoSBOGEUEYNMZcVKgkoNMfUozm+Lq+ttMvWa0z3s0LOle7DHoJ9rCNihXOCUbzgmnmiecGYXWTBxeCk0nOW49HnExLausJpcAJj61KRk8eM7u6YHHriDsvvEw1ueTxD/8aawra+3sMugPe/u5/QhaXBFGH7tFz7D/7MibYRccpWgdordA6IG2l+HxFWVTNSSqKkUqiggitJWEYsDXoksYBx4+ecLKYYYqCaj1ndf4UHXpuHAx5Oppzsz8E9yE1BL/IoX/ZMPL50oZfG35t+LXh15c88iN+/qcXILwn1oqj/S2eXs2Jun0eHV9RGZA6wJmSbLVgd2/I9vaQ2jkenU85m2Zcnh6TxhEv3jqg13KEyjBoh8RRh6vM8XBaMp7PmS9y2nHK6OqSQTvAipDnD9skzhGLmhv9iE6isFislNTGohZL6k7JxfmC3D3hYeuKWwcDVgc9lBasC8tiUfP9H77JPHdcTXPKVU69WFAup5hqhcAihUQICd41CBECJZvvWyoPpmA5umArX4PbxYsAqQWYCmFqfF0gpaTXSpvnzSs67ZgLDV4LAhWhA4VwoJKYVtpiuS45vVzQudGlsJJl5nh6teTkat60vioIA826qLmcrMgL00xbrgVlXjM7PeH0rZ+yHp+TXzwiX6yYnR4zfucvMcWYq/dDrtpD/OQCXy/IfUzcHYI3BEFAq5WiAoGxFUmkGPa7lMJzfDbGIhAqZLVaUltD3ElodSP67YBBO8HeGGL9S0wvrhg/fJ+Td97gh4sR4+cf0M5v8/Ltb9EKJdKL66Xk4O80jt9oo09DG35t+LXh18fVl3zzA3D9xnuPwKOwDLoRN28ccDw2WCcJooQw8KwWBXjL9lafdquFszVZZRgvCoa9Lb5y75BYWbQQSFcTKkE/kpSEXBWOJ5dTro5H+GXG9OqE3d0eXSXpt2ICIRnEkkQKDneGTO4a0lBjyhXVfIrLF6yvLqjzjO7WkEkYkmcZwhmW0xX5csbewR7LywuK6ZJqPicbnbIen2CzKdjqeg6QQugU4UAKjxYC58CgcT7AIxgOO2xvt3ECnFVoEeGspTY1tckxDqKkRavdw4iQ/s1DjBAUyzVJEFIXFVGnhUja5EZxviiI4oBlZnjvbMnZpMB7jxQ1cRjQThPaSUoUOqp8gTMOU3qy6Zzx6WPqyQl2dsY8v8Dka/LZFT47RbkFzknW2SXCO7wQCCy2LqmqHGMKpE8IdQTO46XD5Bl1aZhM5igdQuTwKmC9yonSmG67jZAeJS0HW11m8xVV0aP/lRcolpdMz57yzo/mmNlTfv8bd3nhzjYCz/VPH34xanKjjX4d2vBrw68Nvz6OPvbm54vUSdK83c3vWoKUlv5Wn7efnuAchHFMsV4TpTG3b+3T73dotSKkiLl6/wN6nTa397rstKCuLIUJCVUITl7vpR3y2s4d7ymWc/LxmLP1jD+vMuJWTBpu04lC4lDwyrN7HB70eHwyxBQL3v3Rj7DZDKsEUkncKqJY5kjVwTtJ1B7QacXMRhcszp+wOLmgWE7JV1fY4gLhViBqmvh4AEEMTuPQ5E4QtBKEDgm7O9x+9gEP7h/R321jraMoPWVRkZeeTiviwc0enURxNio5XxYIDXs3b5K2epR5wXK2ZH16jrOQzVe0t4aIpE8uQ6bVmlUpECoBHFKGqDBAR0nTfWA8ynjWkwXr+YKz4w+YHr+Jn5/gyyl1abH5GG9qnFlfJ/0lSkicbbo+lBQoHIkKCVB4D85ZpPdIZ1jNZ0yvFoBmZ/8GBZDVNab2TCcLppM5/c4Opbe0OyHPPbjN69lD6iBgePMmo7MPyMZXnMg1f/bnf8mzt/4XaOkadiD5TYHj8526+fVrw68Nvzb8+nLzaxP5ud7oNhvfJu8ZxyH5ZU5RFEjZOHPKUHG4fYOd/SHOO8BRFgacI9WC3W5CEkgcERdL17h5SkdtLLPCcTWtESKi1RtQLBbEWwPAU3pF7gNmFZzO17S1ZJgGbCeCG8ObjCYZH7z6BuViQmUsPmqj0g51XTWFi0pRF2smF095+OZrrOcLTJ6TjY+p1lc4s0Bi8NbjvEc4R6D6dLbvE/RukVlN2EppDVo8+9x9XnzpBQatkLbJiaOQzFtK4Yg7kl5LsdNyaFnT25ZspSHTCs7mnou6JNjucxFIUg2z8RikQ5RrqmxJHiTURYGyNaGpm5OT8nhXUpuCuq6YX41ZTqZk8zHz82Nmx29Rzo6RxRxXF3jhcU4hUUhhsA6UlAQ6ximPdwaPp8zXLK6ucDrFKslW0iNNIoJuC4Ukn5f0ekOCKGG1WqLiiFangzU1T55e0O21iKIuq7Ki8pKtgwPOTi8IWr2m4HI9YlLP+KM/+g/8y995hWfv37jumJDXP4Q22ujXpA2/Nvza8OtjabP54TraJz70OJAoFSB8RrvdwktDbT1BELO9uwM4qtpwfnbF1eWIs5MzkmfvUpYHlO2Y8Srj6cWM3HmiJMZ5mC5qHj6dMZouwRk6+/uEnRTlHEkcMluVnK89UZTQb8X0E0ckDbaIWMwzrAFTlySdHr2dHYZ7u7RbIdoWrJZLLs/PqJcLAhWxs38b7zxn2QSzOsV7h0AihEBKibGGupyRFXP2727R23vA4HCfG7e2ePbONre2Uoappq08USAxeKyHXgyhg+Wq5vJqiVOCQdIm9IK5KylnV5wvVmTrnGq5xmU5UglWPuMiLFGHu4yvpjz94JSqqEhbbRCCMJDkgClrJhdXTC7OKeeXrC4fko0f4usZwhokAifAOgnu+u2SAmNqnKsbh1cA6SlWY8ZP30Vqwd5+QugSAheQKIVSAZ1Ol9V6xnw2xeAQWmKVROiUdtghTLoIEdKNFB/MRpxO55RS4YOIuN2iVg5MxcmTU/4f/8//jv/L//n/hFQCgfi1RY3/sdPRFyWqsdE/rg2/Nvza8Ouj60u/+fHCI7xAOoUXNY4QbywHvYTTXoFKFdaCVgrrLVVRsVytydZrbFFw9fSER0qRhAE6DDkbzZmsMm7dvcnNbotWqwUip7eoGM9nJEnA3t421vRQQtJutyirNWfTjFaq2baKZQFjE/C9N455950PENLhKLGmQNqcnZ7l+Ts9ApXw7jFUnZq1k+R5zTorMEVJVdXUtsb5xr8hDBRKaJyr8Sajmjxk9H7MdhwhbmyRxCFpoOkGDTjiQIACXwnSEFIN0jemXmm8RSkEp3PD8WjBw8czRucrinVJnpWYyoJV1KbCO8GjRzO86rO1dcSRi1FSU1eO2XhMANjakq1qskWJLzNYTyjnl3iTIXAgZTO8EZriPPmhM4UHYXEetIhBRKhWn6jbQ0QBlbUsRhNMWZFGLZAKF8cgWySRRoSC/s1d2knE1eWS6bygLGsuzi6p8hC/08MTkeWG1XzN7HJMuSoRKkUrCIOIP/nTv+DN/83/ipe/ch/hDAj1Gz87bTY+Xx5t+LXh14ZfH08fefPzy9OP/65JyL+cu/vbH/u7Hucfu+7T1IfP6EXjFuqFZ53nPD45o7d7xO7eDjqH1TLDWktZFKRJxNVkSiAUINFC8t5bb/H44ZtU3kPQYXh4xM2b+/QiwU4/ItSS2kvCNCROY1pxAN4SSomtCkwVcKMX8f9v782e40jyPL+Pu8eRN26QIFkki9VVfU13zS1pr5FmV2v7oheZ6VGPsjWZ/rh5kcnWxqQ9e8a6Z6bPqmIdLLIIEiSuRN4Zt7vrIZCoZDIzkQABEiTjawYyM8LD/ece7t/039cvRxu+ftrmn1p9Do8G/P6zBzzb3kYnQ1IrcVDc2Vrl3/3zn3Pj+iq//Xyb/d092r2QNE4YRjGe5yGyDCFAKhffqyCFJMuGaGMQ0gGbgU6ImtscffVL0DEN17DqKxqeIE7A91y0zVdrrNRdhjH0+wmx1lSqHklm+fzhIY92h3Q6AVIIKrUKpVoFx3UQGMqeS71eRtsMz4P11TIbKzepNeo8fdrCYsmCkCgdEA/bBO1nhO1nDI8ek0SHCBOhhDk+wSj3bK21+XuzAilFPidBubi1TbyVD9m490M279ykXF9CunVKvofjaIQBoy21coler0+WplhHEfZchKmiXEvZB+lYdBoQD1IOyYhT0FGEYzRSZygh0Z6P1gnDMKLsS/7rL37JT378MVKY92Sq4NuLgr8K/ir4q+AvKJQf4PhsW2ExQrB32GL72R4/Wr+F47mIKKFUKhEMA4ZBiElj6hWfsi85OuziepbuQZdeGuJWaqzfvMmHd+7xw7t3+PDaCr4nkLhIp0StUSfRGXE4IBz0SbRm2O9ScgSlZR8XlzCVhKJKzxqM38BxKySySm2jyl/8y3/FTz/9IwIt+cWvv+WffvsVrfaAVOeSpZIKoTP67SZpPMyXSlaWSaKIJOnnK0JEPqnNURKbDsmaDzlIYnSqqVfrrK3USY2LjTT9YYDvu2TSwXEFR4FmOIwYPO0QRJpOPyTOMlxPoUQJ5XpIz0W4DkIJSo5ka7XOtc0GSRiwXC/huIpOP6Y/6DIIA0yY0D7c49nD3zPcf0jWOyQJD8AEYHTuMVlAGI5pA2vBku+uipRYYxB+hZt/9Bd8+Md/RnWljOdKTCawxiCzhChIUA588vFNNpeqRIlmkGnCzPDosEV7ECAyRaVcRjqSzGg67T46M7hWEwR9HCnwy2XCHjjKQWDJ0pS/+69/z//6v/xbtq6v5BVKnH+5aKHaFDgrCv4q+Kvgr7PjQjo/b/vKCZEvosQieL7bonk0ZBilBKEmSzRJYsm0Jk1TfMej023zpH1IpVLHdSpUa0sMOhllr4brllhZrbG8XMLzIYqHJKnBGodsGHB42GZv7znCWGqVKq7jID2ffqRRMuTWco0Pt5ao1weEYYoOU9pY/LKkfdTmP/ztf8LEIVmsGQ4DvHIJxy2hk5CwfUAWDtFBH50GuA6kcUwUheRbghns8Z4OWggsGcQ93PCItHdIr9Wi29sizkqEccpRq4PjSDpLFe59sMoHaz7+Zpmdo4TfPWgRpU7uTWiNAHxH4ZXLSN8hNRlCGKQjyLRBZ4bhICFJNE/32jSbPYwRDAYhRwf7dA+fkLS2EVEbayLE8f71xh6vYxHH3rbJx/6tFUgs1hgQKUk8IE5DpCu5d/cm12oSYTLSLEEYwfazDk+bLaIsxZoUpVNWfZ+l9TL1quCXrR7t7oCl8jpYENJBJxKrNfm6EktmLNarUqqtk8ZBvodIGvP4ySF/8zf/N//X//m/v3HJuMDZUfBXwV8Ff71//PVKS91HWJQ45j0z695lysu5EClOtjewRjIYJgShZhgmmNQS9PoMI80wjAiCPlkicIVgdWUNcDiIm8TRkCTuIkNBMFym0+7ycPsZu/sQpSmRcUgySRRp+r0+K/UlEArX9fBcj1QnRGnGzc0NbtQcgiSm6mWsrjY4rFbRruJg/5BON6RaX0FmEUc734DI0PVllHIYtA/pd5q4SiHSDFcI4ijC6AhpLUKYY5fDHI/rSrTIsDbGRF0G7X2az57wsFoGR2GsRWuQUpKEKZ7jozZruA1BreZSKnlkrQCVCbIkJU1TdJIRhzHSzScoNho1jtoDhkHKsNsj6PUZDCI6wxRtDavLDaRU+H4JtMBqixTHy2GNPd6IH5ACpHPsgTqjioAwCcbEYDNMNCDuNOk1DxDxdW7eWGat7KCUj1SCtSWf4LOUIIRDlaGjgPUVQVUpfrhZobO1wj/uPWLQblNfqjNIMnxHIYSmVq1R8stYq8myBLm2iSMFSimSsE9z52u+2d4n1RLXke8VgbytKPir4K+Cv95v/nrvh73yfrnNVxQgEFaSacNgOOTp9iFHnRCryjRWVvnoB3doVH1sEhJ2W3xx/yuisMege0jUbzIM+6hSg6TfRYmbDGNLKzAYHHSSUfE9bm1tsrzcQBsNVpBlGeXSEnfWK1xf8qkIS2wcUhPQ67ToHj5n0N7PD/1zJCbscLDzgKj9BGxE/zB/hVk0wBhN5laQOHjKRSSATZBCHW+BL/JGZ53jiYQadIqVITYdkgZ99p4foFyHcqWM43gEqWYwTDhoD9m9uc7qsod0FCgoVyVJopBOCRWpfBWDlOgkQwlBa+8QXIXj+qRJzLA/oFyusLJSJ81itM6QrmJpdZPG6i1CHWLiMnFwgNQapHd87LBCyDJSlBAShLTYLEUnfaxNAYtjNIQhve6AVqeH1RWWHYeqa/PN0DZd2nfWaA0hTA3D2OBElvUElnzBj39wjV5sePj4AJ1ZrHSIdYqPJElTEm3xGytsfVwm6nYh01SWKqwuVdl/tEan94g4MzhKHC/lKFDg8lHwV8FfBX+dD+9954fR0SYYQOD4imEYEAQxnnLYWN8kES7rW5vcubtF+2CPw4ND9h4/Ih4MkAK82iqVagMcj0//5I/5y08/YXljiWY/oGIlSWLQUlP1PVZWq5RLipJbBgtREFCu+pAlJJEg9CTtAJ4+O+Lz3/2e5nffkLR2yWxGKw7RWUwW9bBJkK8akBJhUjAxAoVODdJvYDDHdKjA6JMt4cXxxllojdAaKfL9JdJoQBIGeEmK75ewGqySuCWfBChXPNZW65Q9QRqFfHxzg83lMs+OOiRmCR0lVHwfbSU7T/by8WStSZMEIWNc16FWr+G4Dq7v4ToV9g+bhHFEv9cmS4fodEgUh2AsUpaQbgPplhFuBa+0inLrRHGA5+cTLcPec2yQImwMwhAOB/nmYgdNWoMGermCh0EBdWn5yc06rUzy5c6AJwchQWpwlWYjrRIbzdpKjaePDwh6Q3DzwxIzYRE2xQhJYgVeeYmy8Ogc7BG3+6yvL/PjP/szvO4SrpLvDXEUuCIo+Kvgr4K/zoUL6/xMWzkxfn3y3lVYLXFsST4bXxgQkvpSBeEIMJLhYICWCW6tQb97yJf3m3SbLbrNHiY1rK1vkhrJ7Xs/Ih5G7O09I9EZSRoRDHq4CJbLDqYkEcbD8R20sARxjE4NykK30yZNXKjVOHIsXgq92KXfGdA/OMCEPZJhE50MMGkMJsOaJB/nlx5Cumhr8yWvRqFMBtmQRJvcK9IapEBL5zi3EiHt8VEuDsaCRaN1BDbFcWTu/SAxxlApeywv1VhveNzeqFBW0G4l1KRF+IK4XibEJ3VhuVHjsBciXInnutSWSvmG+zpjGAYYKXHK5dxjQrKysoJCEB9sE3efk/X3EVikU0O4dVRpHb++gVdbprFxi+rKNaSvKFcrNA+O6O1u03/yG4aHDxGqhDAa1xiG/ZTH+0PuXW9QdSyusCAyao6gn0C33eX58yNKlTLtoxYugigISeKUKMiQ5QpuzcMmliAIETYDB6JUE6cpjs297cPdPXTa49M//yl/8unP8ByPfG7C+yIcvzso+Kvgr4K/3i/+KpSfF2BZqleolT36/S4HB7vc+/AD7n5Qwy3XOOol+BslqqVlonQIWuN0BlRcxe7zpwx7fYaDIUGS0pDQ8BWpkUQZBLGmH2YEnYR4GCAMlH0XpQOuLW2xUXMwZERakFlDpeShMGThgDTsY3SAArAZFo2VDlI4KFlCSgdjE0wKWgNG4jhlMm2RIkN6VZRTQacxNu3nRC0dpKOQArQCqTyMtbilMk6pjJUSFCwtldjaWubaSoWyJzGZRkvFk8MW3WHCTrOLRnJraxONJYqGLC+XWFtuUCl7ZFqQGUOz1aXV6YNUiEwTB0OsFdg0xmYG16khShtY18dZ2qKyco3q8gbV5XXcUg3pl1naWGf9+ipupcRGN6S7/QHbWciTbotSZZlSrYGwhkG7z/2vd5Ha8tGNZW6t+Kwv+QyTlGZrSK1cwUER9WJwFXEQksYxrgQhLMI1NNbqpMOU/VaH1eUa9eUarW6XOAwYdHqkccSPf/YjqhUHKV00bn7KtDUv/TAWKPB6UPBXwV8Ffy2KC+/8XJWVE4vbcLz8UIDAsLm2xHKtTK9zRBKGLPmKP/34BlqW+Kf7zxikKdKxVMt1jg5aWAvPn3xH62iP5Y3r/OQnP+b2BzfYXK6gyIgyeNYKOWr3ebbXpNfu0Wt1qFQr3Nha48cfbnJ7c43ViqSXSHoJGGNwSwocS5JFSDKwGUopMmPQRmOtwFMSKbx8/Dkd4rgNZO0mTm2DW3c/Zmf7IdGwS3lpFbdUJx70iDv7iCxCuR7KqyO9ElpJHL+BW1pHConreUjfxykpGitLVGtlUuHwrJ3Q6/YZhpowTDk8PGL/qIvnu8S9kJX1Bq4nub25zMbKEkZoMiMIU402NQZBRJZpRKZJo4R2q03YHxBHCdYp4zau4a9s8OGf/08sXbuBUJIoSsBAlqVkccjB9i5xOqDV3OXp578hev4tynEQtRs4qx8glUPFkcTDhM8eNnncSbjZkPzZT26QGcWTowGx9Ll37wYmDfnBrQ06nYDff/6QXnuAzTIqlTKe8BgMeyRxhKtqrK40cD1Fv6NIBgOu37nB3Xu3wSTU63WGUZ9Y50cFvFp9LPAmUfBXwV8Ff71KfXx7cCnKz+sikAtLR+T/CAwr9Qof3b3J7795zsrSGlkK2kC316PV6hBlAumCSTN0rFFW0B10EJ5i685NbtzYYNlTVBUo6aCtpT8IeH7Q5mC/R9gZ4CovX32gFJVKhSxLyIyDFYpUpyRxzDCK0dKnUl+h332GtRatNcZYkPk251JolGuJRAkcn9LyLWrX73Dtg3v89//in3N02GT78RNWr22iymW6nSGPv35I0mtSqZVxy1WE7+NXKmSxot8ZkCQxDaWoNRoITxEmGfutPqmWdNoDOq02YZCQDYdEnQ5JlOCUPVhdplRSXLu1xu0Vn9WGJEg1/cRgtaHkSqqVCnGkCdOIQRgTpZpMg+tXKdXWiHoQJ5LK6gq3f/oJmdX0Oz2yICGNcwk8i1NMljDcaxIfPccmPRrXPmblzs+4/oMf4bkCx5VYKag1qqyvLdFoKA6DjMEw5qifkpGxVq9xe3OZu+s+4VaFQb/Hbzoh3f6AxHSwdodBf4AnJa4DK8tlkjhmoAXL9QZ3715H+R7KKqrVGsGgTz+MKNe992qjsHcRBX8V/FXw17uPV9rhefLa+PVFw81LY1q4yXuzxuoXxvFxJvl6CYsrLUvVMlkcEoQJzw87PHjSph/GDIIEI12kUpRLPhXP46DXJQpjVq5t8cGHd1hdruA7Ap1lBNpw0E/oDCIMAsf18SsWR1mq9TJ3b99geamGcASDTJMiKTuKjaUKd2/f5sbNuzx8+hhjJNqIfMmkkMjjjbMSbamtXae2dptGY4V7P/gjtm5v8dHdDf7oziboD+kOfob1fAKheHIQ4tZXWKn5rC6XUAqccplBnPF8p8M//P1vqIUJyzrD2AxXOoCkP4joDWMGgwCEwvFL9A+bDI+a+MohjIe4rqRevcW9m+vcWy9RUZYgc+gmkmEp3zk0CD32ogFGKSiVcRBUGsuEfplanFCqLtMPQr784j4rN7a4/sFNSpsKKQRkltZRl4P9Q2SpxsbWR/R3HjAMmkTxkMHgiGH3CLG8yvqNm1TrLneul/iTT1ZxFSTWspNF+K4LiaamFNcqJWpoyj78+M4mXz84oN+PSJKUQauLEOAoAEO5XCZJm/R6QzZWa1y7vkY/FcgswXEUxvPpDiM2G36+JLfAlUTBXwV/FfxV8Be8xXN+LswzO96Byo4oxGSsrTQo+R6D7nMwKV988xjheMRhSqWisImhvrbCbrxDOByCVCxvXKPeaFD2HYwURBaGGXTDFLdc4fqmC5nkKEtZWirxo0/ucn2lwXLJpaQkvquQ0sX1NJGBR897RNEQsFjh4PkVpIQ0idE6RSqFV12jvv4h//zf/DU//XiLW9euUS67NDzDihujXIfrS2VSIegmkjhWfHhnlZ/eXueDtQolJRhmhsftEIHH3U9+gKvAr1YQGColB69UIs08rIB6zUNrSX+QkA2Xidtt0ihG+S7KccEKTBpTUR41x+JKgSM0S76i5pWpljwqFY9OLyZILb0gJAozUlVmuVbHJyXLMow27Dx6Thxn3Lmzzp1bKwhjuLFS4vmSzzA07PuK59s3CIcHuQRORtRr43s+neY+N6/d5qd3V7lRMrhS0k8tcr1MlFha3QErdZ+ql0vvrmu4d7PGBzdW6EcppVKZNE6QNiOJE4aDiN29I47aXTTQWKnj+S5plKK0IUsTEJL0eCuS0QZn+Q/T5RDJZSsT76LMfZVQ8FfBXwV/XR4Wif+VNjl8UwR5kelawFqTv2grsTbj1maDmudgEk0wDNh9tkt9aRVQpHFCGIUkYcTesx0QDuXaOvX6CkGS0eznSzY9VyKkQ6lcoiEyyr5Pw3ex9zZZW66zVPZJwz7SODjG4gmBwnA4SHh40GPnoEelUsZYjaMcfM8jinpYq1HKR/k1ZHWZux/d5a/+4mM+uVmjIgVxpglTwX6QUqtYqg6UlIv2XNarLn98b4MfXyuxWlE4QtBPJEZUSGyJg2aXLEipNxo0lqo0amVQgkRneFKzstSgF8XsuwO0XiEzhrDTxxUZXrlEu9Om0ykxXPUo1zxcIXKbMKz5kqrjUis3eNoJaQ8zVmWNw+aQ7iDkxr07fPJBnWUP4ijl8W6PZi/m2bMODV/x0c0GTkWy3NigF2tubjVIs/+R31mBk0aUG2v4jRUqjTo2Tei3+yh7jYorKWFwjcXzLWbT54lIqflQ98FzoORYrtUVn36yzl53wMr120TBkN5Bk06vzSrrtNsBUZgipSIVLt88bdE66FNxMuLVMqu1fHKksRZ5fLp2Ph6hAY79cnNh9bbAq6Hgr4K/Cv56v/nrwg82PS/Os+PqRcaX75IqEAKUhHAY4pUqSNcjjlIQA5TjEgQhnXaHKBwQ9oco6SCEwhqJsZIwgzTT1Ku5vCxVmXrVIKWPqxxSm1J2XESWot0Sq40qShiiDOIkZqcT0gwFRrpkcUQWB0DGMIgwJsGtLOFUtqhs3uRnf/op/+5//hfc3VyiRoaDYGgddvoRT5o9ri9V+HC1RKNiECqj6mQ01kuslhU1x4LJMK5kpepiWwOiNEBj8GsepYqHxSIyg9AWZcAkKQ6WjbUllHTwpaT8wXXKJUUQRQT9Lvv7RxyslKiXlvGUBSGxmabsCEpK0A5jHAxLFZeyrygZn1bLQ9uAO2tr/PG1EkIJnt1Z5rcPO3y71+WrJ0e0+iG3NpeoVV00gsqSz51PfsiDz75Gd1p4fo3Vzev4voNOQnq9IcNBjLtZwhcWRwocAwgHm1WJwwhfGmqewFMCD8tP7qzyaLdHK0soVUtElRIG6A8G1FeWKPseR90m299uE4VDkmGITkI2b23wk4/vMEgcMmNxZO6FW0Zn5BQqylVBwV8FfxX8VfAXvMXDXpcFayVhYjDS4drND3C8Er1+wGAY4Mh8aWU06BIOumRxCq6P9X067RYrm2scNbusVzcRysGRUC85VKXIe9U6RWiNKx1KJQe3Us974ii6UUYYGXDKNOqCR9sHHDU7+H6Z1C+hkx4KjeNUqCzf4NO//Ff863/9l3xyq8aSa6lIgRYuvdjwuD3kUXNAN9RgYGvFUq8rSg4ooZGAsQqDJLOSRIPEQSCo1apkWtMfBHhS4UlFFEVEUYjRlgyLWy6z0aiyVfO5sVpjpa4waUav3cOxmpLrEccJylcYFEGiaQ00BkGUGnygrCxrJcH1rRpKbhLFER80HNZdgyMty+uS1fIKK0su3x6EPH7e4sGD56zUSji+T7/Xp3twRNLrUfIbCK9GmqS4rsonXgLd3gB0Ccc1SEBKhXXA1F2SkqDkWlxlcUR+9s2NJYc/+WST/+cfH2NLKzRWlrn94V1aR016vR61ag2jNc8ePCILOwhpqVYbVEs12u0+vaFHZgRWWoTQcHKaM2P/FyhweSj4q+Cvgr8WQ9H5wR5P8BKAwaIYhhmpVdz56GOU4/PVl18THbUpeQ7RoEuv1YQsQgLWRARoEgy1pSWUEBw2qtQbNeq+iyMk2HzjKNeRuK7CGItQLonOOGp1CTPLME1plMtUfAdXWiquROMi/BpZkkGqEUqgjSLODIPhgEbFoVGS+G5eMRNtafUDWv2AOImIPMl+V1Atu0iV4mDwXAetDW0t2e8bnh50+Ha7ydePnvPl519y/foGyfUblJZWKFWqVMseUTAgjmKSJAMBNW2pVX2urdbYWHK4UYWSUqiNNYwVpJkGY0AI+lHKdwcDHu11ieKYD66vs1QtoZShhML3FHdWfRwruVlVuI5AiQRlU25VHWofNfhoq8FnqzX+49/d55tv9xFpzOGTh/SePURkIZV7PwKZEvSOELZOpjVe1Se1kkyDdQxg8gmKUpBKA1VJ1QPnWMqVGEoi46MbNa6t1XncSugeNvGASqnM0X6TuBrhCId0GBMNAoyyNBpr3P7gBt98/Rm/i5r82Yd/QbmexyesxR6vxLkI7+kyh2mKOT5vKwr+Kvir4K/zxH0p+/zMwkXtkHpxcvXxyg7y1Qf53EHF871Dltavcf3mTXaePicMA8q+RzrsEXQOiHtHoOP8HGXlQBxScRz2th8z6HRoVD22tjYwOsMREs8TWEegRycSJxlZBoftHs39JhubGyxXfFarDjXX4LgO8Se3ePb0Hr/ff4RSZbyVD0iMRS5t8MnPfsoPP7mLLwwuBmvBKEGiLdpaSq7P3U2fZd9hrVai5Ag8mXsknidIreAwFvznPzzlv/7yc3qHbYLDJu29bdoPfktj4wYf/vxPqW9ukS0tkUQRlXIlJwVr0GmC51RyeT2MGToeoixxhMUaDUKgcegHGdvNIdt7bcIMEJIszYiCGFxBGCdEkaWfpHxyrYpPijAm3xNESDyTUhcZq57D6pJPbW2ZcBiRxSGVUo1eEqKHu/R3UnrN76gtb9CVPrgl/NKPMfY2RiiMzRBCggAlLL4CKyxKHE/uOz552VqDrxzu3lhne3eb3sEhg3aLWqlEHMe09B4rS8vUGg0Sm+D5ZVa3blBbqWKF4P7nD/nuTz9g5Wc3ETY7PncpJ47TaupFDsEUOD8K/ir4q+Cv94O/3nvl58U+rcUgOTzqsby+QavX5dGjh/i+RzboM+w2GbT3SYMu1uj8YD0hUOWEoZAEg5B+q8VnCvrDIfX6MhW/zAc3N8DNicZgKAmQQtEPE5aWG2wtl1kpC3xh8FWGIzW3Nmrc3Kjznw+fopXH0o173PnRj7l77yZ/+fMf88Pbm6zVJCWZ5me3WEmcZaAUSjnEQYDruyyXPNYqirIvCLWlk0CYGJ62A77aOWK/F+EKD2MVyvHIkgGd/R127gu24iHR4BpJKqg1EqrVErVaGd93EVIQJZokSuj0Q4QwrNbKrNU8Kp4kNZb9fkhrkFIq1XAcRZbEhHFGZxCTYBESmu2IVndIEixzo7HFjapEaciQRChaieFJJ+Kb7R6H+02Sfp+ofUga9rE6REdtBnsdcBz6+zVcd4nG5l1s+glaOAwyS8XNJXytQR57yAiBMZDZfBmuBRKgH0MUxITtJll7n+HuLjGWzGQEccKgUmZ5dYPacoOf/vGn3Lt3jVJJEfVDth895re//Zw/+dnd/DxDM5KNTT4pw45qXIECF4OCvwr+KvjrfHjjnZ/xnuJpvcbJPTgWjXdhW4Ak1XQGId822wyChHDQx6YJRwfPGbb2SQYdMBFSCrAZ1liSAKRbY3XlGpWlVaJM8OygQyN1GfabfPHtYyo1j+W1Fa5fW+X2+jJSOlSrZVaUYdVNcW2utCYIQm1ottv89h//jqD9BN91iaNNnFKJn//8x3z0wTLrfkJNKpAmn4dvyQ8BlIJB1OHps13WG/co+YqKm593M4wVv/p8myfP9jnoR1Be4t5H9zh4uoerPMorq0S9JknngJ0H39A9OuDmj/+U0tINtLF4rkTKCtZaojjFakOj6rG87BKGKb0go1b2KIs8D8Mko+T7aGEYxCmJUWRhTCDBTHIAACmgSURBVKYNsdGUfZcgjul1BzzYMayvVOlvNnCBQRxwGMQ8PQrYaYbsPesSPDtA9zq0tj+nd/QEgh3IOoSpRKkSrnRw3Dphr8/O0z0ePGlyY8mldKuCJyFJM6qeS6I1SghiYzjopwinzCCMsJ7Hd3tDHm3vs/90h+6z74haR7hKklqN4zjE3T4HYZf69S3WVxw+vrOCTjLu3bjBg6jP73/3OeH/9u9QJYu0x/VUjH6iFlMV3ibv6X1HwV8FfxX89Xby1xvv/MAVKCwh8oP1LASZJsSl32sTDgOGrQOiziFZ0EMPj7DpECvyM5SVyBus61UoVZdQlQaNrVs0tm6wuV5nfW2VVjfg/udf8eibB9y4s0Wt6pGsNPCEoawMqzVFreQwTCy9YURkJU+bfb74w5d8+Q//DaUHWKdGFofsP9kh6Axwby/jYHBkThZCgxWS1EqiNEVZwVqjwa21Bps1H19kDAw8bYX8l7/7jOc7O7i+Q7lRw7g+jeUlvOvrCCvJ4oTe8236rScEzR2izj2qSzdwPY8MSavVp9XusbG5xtpqA+nkZy9L5ZApSZBaVGgZBCmu61GruawYzVJiOehE7PYHBFEMUpAYCDsRDCPaccwvM8N3G0soKen0h3T6AWliiaOUeBhQIiETETo8wg6fYeMWAk2+yDbDakMY9HEyGBzs893jFj//5CbNRNBsDVkq+Xy4IiETxCZDKJfPtw846O9Sqtdw/TLfbTf59qvHDA+apGEfR1iM1jiOQkiJtMd76aYpaRRSdaDRqCL//Ef8/d/W2N5+TvOwRf32EoyWhloBVo2W5Mytim+8LRQ4M974Oyv4q+Cvgr/OjAvp/Jx159PLGB8/35jj+Ez2fFwzSjJWVlepHQxp7W7T2f+OsHOEyBJ03EeSYYXE4gISq1ycch13aZXq5jXufPIRW1vr3Lq2TK3W4NefP6RcKeMqxaDTpXnYQUcpmxtrfLBWoVpSWGHpJobv9vo83jnkN7/+NY8++zVhaxeFxmQaIS21pQZBJtjrRVQ2fFyghMJKyIxA2wwpNNeuLfNHd9b4cL2E5xgSK+mElm++2+Xx9jN0EJAFhu7hPrXVdbwtD3+pTq2+zKAz5Nu9bcLeHo7Q7D//DspLLIsNknRAHCc4XolEWzIDgyDkCYY4NdSrPrXSOnGcUnYd6pUSxlgyq0mFQckIVymUEQRBTGvYpflsj6C5Txz02a+U+NZzKNeW8at1kC4ChU5TTByTBH2Onj1i2N1HpwPQCVIAQiCsIYu7SCdClmpUG8u49Trd2PLLBx22n+/zr/74LtetJokz+hngOCSmxH/+xa9YXl/lo48/IU5hGA7JTIyQAm1ShDVY7aC1ACEo+2XKfhW/VCUxgp29I7r9Pm65xO6TAx588y13bv0ZSkA+IXWstk3x+t8mwngXUfBXwV8Ff71//HUllJ8R3sykKQFIhDVoK0mNoVqrMeh1GBztExztkcURvu/lPWdUfrKvcgCBkR5+ZYlytYFfqrK0VOfGeo1GSRAEfVAOpVoD1/foH7X4/B//wO27H7JcW6IkoaRACsFBL+a//P0f+PIP93n67eeY/jNckZIZgSsUyhqSOOQf/ul3HB1dJ/j0I+6sl7nVKOUT4IzFl5LVssNS1WOrJmm4GbGVtGPB4dAyiAxCa6TNJU1Xekgc0jhDWTBxQOvJA7rPvkWkfZySjzIpcfuQg2CAdUuUanWW10t4ykFYSGJNqVwijgfEYZdmvQI1D1calMlwHZdAW3Y7AQ+eHLD75BlkhiRJyeKY9tMHHD76jCxoIxwXpVz8xgarmzepNJbRBjzXo9NqMuy3GRw+wiQdpE2wGIwFyBAmwxEWbTWpMSAtURrxaL9LnGVU6xsc9GKaZYc0yOjFGZnI2NlvUl9apnnUZWm1Q7c7pFTyKPmKUCdYHWOMxvcaKMcH5VBeWeaHf/wp127d4he/+Ef+/j/+v7T39sh6bdAp/+E//C1//Vd/hpA2H17Ia/VrrNMF3gQK/ir4q+CvtwevtfMzbVzwPF7UomFnxf1C2kICFiFAG4dEazrtQ3qtA5Kgh7SGklfG8fx8l0udIBwH4fhoIxBOBdevs7y0yo8++pAffHAD39fEacYwAadUJbOSzEAyHEKasr9X4WBrnU+2qhgrSXF4+Og5v/rFL+jv7yCzHkiNtRLleEghCXtNdr/9jP2dbeLeJxgtiH5yF3VLslFzkNJlEBuSMKVeESg8Aq1oBhmHgWG3oxkMYkgCwv4RsRTUllcRQpAMA4KjNp998Tv2v/k1uruLSIcYV5IGbXrPM7zGBssffMTm5ibleg1rU4JhH+UqahWPaBAQRikPOGTHV5RLkts3l9haFujEcnjQ5cH9h+w/eoRrMzy/jLVwtPMdaWcHkhbGWjIrCVuP6e3ex680EMpHCgedZhgdYeIWIu1jdIxFY5FYo5FC4/irqNoWUSIIuwekvTaH3SXiJGT3+R4HD8D9y5/iKUNmLGE85IvvHhFrD7/aYHf3gKA/pHt4yODoEB32MVmAlC4GgVAlltY3uPOTT7h19ybPHj3kb//mb+g928ZGAxyRUi57/P73n/Hdox0+/viD48ooEfb7qalvq6f0vqPgr4K/Cv56d/jrSik/I8w7VPAsBxIu4onlr9RgjGWQwF5rwHffPiTuHGHiIVJJhHKRfgVjbH5IneNSv/ETHK+G65Wor6yxeesGP/3pD6jXFIm2DBNDPzR0O32S/gDHaEw8pDtok3o+R4OAvnVppQo9zPj1L39Jb/chTtImsxHGGIw2KGFJ7QAzDCELEF6ZZyagc9Tk+c4O9t/8D3z68Qf0gpAvHu8zjBK21moEbDLsB3y3s0c7SOkOLI8fPaN3tE/S3UUoiU0H9NoHuH6ZtFlh94u/h953KJNihCYKNUlmcFWZzCZUNjaJoiF+tUw0COi1OqyubxCXBjx9+G2+EVqyiaNg61oDhzpVF5LMYdju0d55Tri/S5QO8WtLuJUawmRgMnQW5dv0W4HQA2zaJY7aCOUDElc4gMaYAZgIY7ITCVYCQlj86iob9/6cw+Y+7d1tnv5OEoQBUZzRO2pRq69gpMe1axWyKObw2SG7uz2cUp211WXIItJhl93trxnsPsY3Q4xJkX4dpRS1pQYCTXPnO5pPv6Z3uMtg5zvssAM2IVM2975TwT/90+/44Q/v5Hk6WZMzf9JggXcDBX8V/FXw19XHlez8vE5YTP4nFP3YsNfs8+zpDr2D56RhiJT5TqJeqUYcZ1itKZeq3P7hz/Crq2gjqNSrbNxYRZYUCI2SCm0F29uP+frLB3T3nhEcPqO9/xTheSw7H9LuBXzxaI9up8Zv//Gf+PUv/iM2PCTVA4zRWCsQWmOkyfd4sC4m7iH1gM7zgGG/Q5YmfH3vIzoDw+Ptxzx68pQkSbl+bZ2P7n3Igy++4OG3D0niBCGrdDpDwtYOIu0hgGE8AOmQ6YyWSTDDPaQJsEiEBIcMmXZAh2Q9iRpuUDPLVFNLr3XI3rPn9GpL9K+tsPP1A7Zu3cIEEUe9Hipaolnusxw3aA4M+49+jx0+Q2VNTBYgshQZB1S8mMjGgD6etGlRQoCwCGnIdIjVBiFzgjA2BasRUqKPyVyKXHoPox54grWtD3h88Iinn/2CsLOH8pZIkoS4ssoDkdHtLBO1uuw+eoSJI/xKhbji0T7aYdBpEnea2EGHhBSUBSXxdIRrQjoHhzS/6yB1jEmHmDRCmBTlSLR00FqjjeL5832MGS0RNYyI492hjgJXAQV/FfxV8Nf58No6P9O8l0Xls8uW2SSCxAr2Djt8+dW3PH/ylDQc5pt7SwevtExjaZM0jEl1gtYZBzsPcet9jCqz6WxhLPSHMXEcI6RDsxXy5OEjdr+9T3Cwgw17kAQIm5INOvTbXeLY4vk1sswy7LUgDRDkBJVvXpXPtjf6eEKj1aRZhI0isjjjMLP88r81iOKE1uE+0aCH4yjiux9y+OgbPv/1r4iDPo4UuG4VgwPREdgEbTREAiEESkGSDhFmiCHLJU4NwmqstRgi0rTH9u92efrVf0EJyOKAJInQGhxpMNayW3KRjnN8TfGffJeK76KdMr3YkqUaG4VonWKFxC+V0UlENGghbJJ7u4AWDigHRxiMNViTj4MLAJnvdCGPt6AQWJQEqTQiaxM0v2Bp6RYrNcGg2aH3+DdYUQIl8RtbDERIduARtpt09rbJhj2U45CZmCQZogS4GEQak9oUZH7MX6o8DoImaTzAZhHoFCF0fgSgEAjh4aoSjhRoA4etLtoYpLQIq7CYmUMZ78IBm+86Cv4q+Kvgr3eLv17pVPeLMmJeGpcR98h2IQQc75AZJYKnO4fsPNpGD3sIDFY6VOqr+I1NEq2Jgw7WRJgo4vDrf6S+9TFbn/wJn/78E25+cI12v8tBPyFKDN99/R3N3ecERzsE7W1IQoxJETEcfgfC8ZAf36Rsyvz1v/wpX/zdbR5/1cKxOj9XRSoQIt9sykqyLMZgsdbkB86lHZJOxrMvQoJBH5vFaJ0SCNgOHpMFPcJeG2xGajMioRDCwWqD0RGQN0ZjNOakZ68nSsrmO+dbm6udkYAuIEDKfImoEpw0oGx4/AWLRhADHSGwx/GI4zIXUqKkxKQiz08WkWmdH8qoFEKkoAWZHhy/sLyOWUvuUYpR3cj/14CxAhMOCTo7PHc8sKB1jMDmBzcKjzTcJ2x/g6ME6Ig0GmKzDC0VQoB7nOu8FAyQgpbYWKNFRpZlx/XRntiAEBjhkJqEquPjKQftuuy2+rT6AzaWq1gz2irDTl0tUeD1o+Cvgr8K/nq/+euNDnudZQLg5cCCsGgU7UDz3ZM9gn4HZRKwUK6u4JXraKOJoi5Gh7jKkKUphohBbx+/pCmVJcOwx8HhAZkRZHFK53CHNDwii5pkYS6VYg1KQNKNCQ/L7Hwp6D7ULK8u4ckAKUKypA/WYmzesBAaY/LPAnsy/BoLiaXJoLMNJjv2cgxWQtgRoO1xw86XmWIF1kqsyRv+97P3v28ML4/niheuCyFO/qSUL3yfhTwtTp6f/N9aSaok4piQXNd94RkYEcdosp14KZ78fn7yM1YjTIIxBnV8JpGweR60UehEkFiLwiCMwQpBkuVzJl5Y0XCcJWsEQiiioI21IJVAIBEi33hNSIlUDo7rM9Ahxjosb9wmCDXNwx7XVmtoo/N5qQXeKRT8VfBXwV9vL67snJ/LltK+j9+SGsGjZ22eH7TJkghrNQiX2soaR+0uP/6jT/nu4UOU8kniLtgMo0qsLS8hbcKTb/9A2VeEwwFZkpDFA9K9BwS7z0la36GDFsYkGKPRaGzQ4llwxP7Xf49Oh6AUaQbCJEibgRW5X2OPx1zheJPxscmSCBASezzGbDGAxpEqpwMpkCKv5CPJEgQoeewp5Xl/kRzy8CdpvNDI7VTyGL8/bQdbKeXJvdGzo3CjOBzHObnvOM4LYSY9dGun22SMQan8fyHyfAohjz2/4/BSYDA5gVqFsA7IPN40Tcl0NllLEPK45G2aj80jjz04lcetIUsESSyRysUtrZBqQ7cT8fTJIT/55CZS5q/RHMf5JlEMdb0eFPxV8NdkXAV/vTousl29ts7P5MqFRQ4GfB1EbZD0QsO3T/aJ4oRKuURvP6ZcXaZSX6LV6bC+XCdYr7PfF7SHASYLsbbL/qOQ/Z0vyExCOuyiTIbJNAZDlmms1kiT5XJhPqX/e4k2TjFSIjAYk6KEQkhQecBj8shl7RdLYeTNjKph3tiFsQjpohwF2OPe/fFY+/FGVTk5HHtkUzDLC7LWvkAWp4Wf5UlNGwYwxpwQzMhjGn9+8vOIPMbv5eP+ChBjXuEoXC4vH2vPSHJvJy9bEDL3ujxPIdLkxTSPVd6cX7+vt0LkkrnB5qRtBZZcHpcYdBZhtObrrx7yb//6T+E4zDs1W/A9Q8FfFPxV8Nc7hTN3fhZZfjkt/OiZ846DnzXdeRi3Q+Px7c4B2892CXothq19sixG65A07NHwLV/89v+j09mj13xKFA6wWYrrKGzWQ1uLxiCFIdU6PwzOCKSwJzKvFRar8sMAhXXIx6stQlgs6mTym+R4EzKRP48FjCVvLzmp5OQxkjj1cX4EVubSq+uoXELNlxeMl+D3pGO+b1jjNTq/P+adTbyrV5H5X+XZF9/5bJn6e/vN8TPyuOGbfIlvHhvCWiwiJ4Tj/SukFDiOOqkbIBA2L1MhRh6mPCFgRsQxescopFSkOiIJmwykw5PHD9HHW8uPfN9XxUW2g/cRBX8V/HUeFPz17vHXlR32ukx8Tx7wvNnh1/cfs/PsOd3DHZL2PjYeMEjaBP1nZFGXOAryBm1TVD7ojOO5KCSOPe4vC9BS5wsctAZh81UHx39GiHzmfD6/H4EhH0jNPwtx7O0gj3nC5J11wbFzdPzB8r2UafLGYU9k5mMZFXEc5uRhRqQghMXK3LcaeQbfh4HxCj5J/FcbNvdQMSCOG7UFONZsJQjkcVnlxH3MLLljg0BIlZchx+Uy8jClzcfHycfLR+nlBG0xNo/PcSSeK+hHTazRZOm94x8Iw2hyY4ECr4qCvwr+Kvjr1XHmzs/47qKzJMNpO6HOi2sWTivs055/wY5R4yKvGAaBRvHF14/56quv6O4+JGpvkw1bJGmEMSlIiysNJVcCEqOd3EuSAkc6eWWyuSwrrEVJByPySXv5lvPHXor9fmnjSBq1VhyLmyOJd1zqhJMdFcTxZyG+l59PPCh58syJLyTypY3jE+tOYhw1luOVEt8nN76R1ezyPY/kf54GM3v33JGNduw7jIjCvhBuzCs8LpPjwjwJe1LkOQN/H9fJc2MrM0YPilG9z9+ZtQJrNZK83juuQ11KknTI3btbqONjBBY5FPCicPWJ/s2h4K+Cvwr+KvgLzqn8TBp31h72NOl41pj6hcjEjKrEsdxn863BtJActVpEvSaDw23C9jOkTcFalFI4SiKEOrHXmLyHrJRCHl87Htb+fvzW5rPr8y9wsj+CMS/k63im2vE1GJ+oZwHsMX2M4h1V/O9LDMRo0hzHRozKdjzgi5IrjLWT4/snMujYuPV53+MkJn9kzkom4zZNuTtmzEsfTsoOe7zkVUy+A05+UI6F5LF4T+gYjn2m0b3vn8+fFBwTtbUYIyj7JTAh/+yf/Xcn8bxrXtPbjIK/Cv4a5aXgr/eXv96bpe5irEIIke+qqYDbNzZIh03C/iFK6HxfCqGQ0sm9nYkxZCnlnMr8fbgR5oUdn/D2oq0Xi4vsSU9OEhx9Ni+R45vERHlO+SGa5fULIU7yMgvTVIPv3yU4juKv/uqv+PTTn5/L+gJvBwr+KvjrclDw1+vAhXR+LqpyTsqFF1URTwTRkfInOF5SqPnRD+7Q8DQlmYFD7vUcT7YTNrdlchnkInL2JDGcd6LkeJyn5nNByf485TqZn0Uk/0Vl/VlhL+z9nyGe0fud5vGNL3kdx2glyWilRqnk8+///f+B73uMfnzy7M1WHGahGMK6fBT89XI+Cv4q+Otd568L37roVTN7WYUlRjPbEYx22VQClqs+nsjwHYHrKJRykFLiSDk2w/57uxbxmqZVinE5djLMODmdF6PnT+v1z0tvnBhm2XMWWxch2cv6wZiVziSmea+TG5tNI+XJ65Pft7a2JtK8uiRQ4HsU/FXw12R8i9hR8Nfbh3MpP2ftiY5wEcQwa7z9tMYAnEySEwis0UBGr9PiyeOHGKMRUuU7k5qRt2RefH6GZHrefL1qQxlV4sn0JwlqvLc/rSFN5mPSU1wEF+WNTSPXy8YkCUzaMFnG417UpCdlrSXLUrIsJb88SeZXQVZ/v1Hw1/T4z5OXV0HBXxeDgr/Oh7duqfu0hrqIVDqOfOJfvmjz88/+wGAwOJGK830TDNaalxratG3LF7X3LA3iLBLqeIP/Xrqc/ex4hZ8kn1nkeBabZhH7tLDT4p8V9rIwzYbJXV2n5WlWvqw1ZFlGmia87C29O8RR4Hwo+Gt62IK/zoeCv86Pd+rEjvmNefTivt8SPdOWX/3DrxACXNfFGIvK13dyvK/oCz1kON1DGFWs8V73tAo6L56zeivTPKfJ71LK411EZ8NaizHmQhvwpCw8+jxJFqO034THNGnbuB2j7+Ny/PjnSW/PcfKlofmKle83dnvXiKPAxaPgL2Z+L/jrZRT89Wp465SfWTjdi5l8eYJ+v8/9+/fxPI8kScCOtmKf3hhnyZuTkuIozLTw8xrntGen5mRBuXpaj19KOXNlw0US2iz7pkmt4/fyM27mk9xZ7JmHaUR+mm3j73yaxy6lwvM8PM97Ia7zmnvRwy4FriYK/noZBX/NR8Ffr4Z3pvNzVggh+OKLL+h0Oi9VgvFGPuvZi0j/MjFJEFrrFzyA09Jf1FM8CyYb3Kz7ly0dT5OCF8HIAx1/flKut9aSJAlRFF2ozQUKjKPgr4K/zoqCv17ElRn2uuhe4aTcO34N8sb0q1/9aiGpdNreGPMk22key7h8PC+tWfFNSq3TvLVJnDZOPQvT0rqMXvsi5DyrLKfFNf43eqfTbJ+X7uScgdPyPnpGa30SLssyWq3WzGfmYTIfl1n+BS4OBX99//ysfBT8VfDXVcKVU35ex5ipMYbBYMD9+/fROj9cb0QOo0qwiOcw8rDGw53WIGZJjovme1bYaY1s3jOja/Oee1WcRl7jZTzurc7K43gZjj8/La3TGtu0OEZ1YPydjr+reZMxR/+PwvR6vbnpF3g3UfDXfBT8VfDXVcGV6/y8DgghePToEfv7+8CLFWieXHxRaV9U/NNIaFaa4+FPe2ZR8rxITNr4qmmPN/TzlPeIwMbnGEzaOR5OCIFS6uR6kiTntr1AgXko+Kvgr9NQ8NfpuPTOz6s0lMtsxL/5zW+A3FNyHGemPDuORXrnp0me0+6d1WuaVy7TwoxfW5RgJu08Ld15+T4t/LTv49fnyb7zPMDJse1Z6YzimPzhWNTG0T0pJVrr/OykibH1i8Zly8hXUaZ+Eyj46/R7BX8V/HVWXAX+eq+Un9HLjOOY3//+9yez38cr2Ohvsuc9z8M4Sw9/vBEvKnXOkoCnxTOeh0Ua9CSpzMrLaUQ6GW7R+EaNfPLztPvzbJpGmLPKeBYhzQs7+d5mlfm0H6ECBS4CBX/Nt2cyrXm2FfxV8NeVmfB8HpxVVhy9zKdPn/L06dOTXu4sb2mRE4LnVe55Np/Wk5+Mf/xvHuZ5fpNhplXwaY1jVhyn3TtvAzpv45tFPrPsWySO0Q/JyBOa9vx4GqOwvu+/Nsm9wNuJgr9eRsFfBX+9Llw55WdehT9v2PGer5SS3/72t4Rh+EK40bjoKMwo/Gh55WjXzMl4FyGYcUyrgOMS57yGf5qnNulVzcIs72HcvrNiWtnMurdIOvNsXMSGeeUw7g3Nen6EaWPvk17deFpSSlzXpVKpvFWe09tk61VGwV8Ff51m4yI2FPx1NpzH1ivX+TkN8xrPaRAiX9L3hz/8ASHEC9uAT+utj+8rcVZSm2ejEOKFSWijZ2YRx/j18XjnyceTz042pnEPaZ6XMcv+yfinpTkLI3uVUidlMUuKnZXuWdKbZ8dpeR7fLXVUVo7jvDSJcJL8q9XqK9XVAu8mCv4q+Ous6c2zo+Cv8+PMnZ9FeubTwp/2zCK95It4vtfr8fjxY5RSZFn2Ug9/nr3ziGJW45wVfvzzoh7PeCWeFXaa/Wd5Z6dV9kUaw7wws2yYtPuiGt0idWJReydPth5hGvEtssvrq+A8ZVyg4K9pcRb8tXiYgr8uBleBv9465ec8GG88T58+pd/vo7WeSjjjkvGkPHgZmOUtXQRm2TzpCYw+v8le/iShXgTGy/Q8cU6WzbgXPY88pnmCBQqcFwV/Tb9e8Ndizxf8NR1n7vyctZIvGn7RXv08b2aehClEvo/B/fv358rBk5uFTab/KjaOy4ujyjg+EW1RzCurSU9uVvhpBHJa3GfFoo33NFsmG+oiNs7zYM/y/OjzaBno5ByJSW9q9P9le07z7C0wGwV/nd/Ggr+mo+CvV8eb4K8rp/zMk1rn9aoXkQeNMXz11Vdzw096MotW3Fk9/5EHNhnP5L1FG8U8nOZ1jKcxHnb0/+Q4/rznx59b1LZp1+bFN+3epAQ+TRJ/VY9pli3z6t7ofrlcxvM8yuXyudIt8Haj4K/zo+Cv2c+dFQV/nY4r1/m5DIx6voPBgMePH79Q8aZ5Oa/SSN4kRiT0KkR02fme1egXlVknCWcaLsvuSZIdX0kx7gFLKV86FblAgfOi4K/FUfDX7HQL/noRl9r5Oas89yrX52H0Avf392m32ydxjHbEnDzzZFqFPq0SzJOsx79ftlx7mp2nSe+v6g0tGn6eR7no8xfhbU7GO4lp9k0bchjVlSRJWF9ff+2y8XnwJqTmtwkFfxX8NSt8wV9vHq9adlda+Zkm3U67vyh2dnZeIotpPfjx5YGja/PSOosdk3kaHUw4jajO83IX6a1PyscXjUlpepo9k9L6afcmhw1et0cysmO0vHjcQx23RUpJo9F4K8ijwOWi4K+Cvwr+urq48M7PtIo/69pFVtxZ8Y2uW2v55ptvyLLsJbvGMY+w5lXy02ybZ/O0RnFe4jgt/dMI+SIwrVHNSnMRm2d5m7PiXCSN8+R/mmQ9jfQrlcrUE5QLXH0U/DXdtnk2F/w1PY7JzwV/XS1ceOdn0Up/EbLwIgQ0up+mKffv38dae7ISYlYlP4+ti9q9SM//vKQ66bFMS3c87Fkb0Fnl1Xne2aJpz/KcFrFxHmmfB/OWgI7ntVwuX4rndNkSeYGCvxaxefz/s6R3Ggr+KvjrdcQxwpXu3o1Lc6/qSRweHrK7u/uSpzL6Pv43LY6Lko3HMW1Pjnm4KG9nURK4jPgn05oknVnpj+Y3nKcujBP2WTyaaeEnCWxkz2gcXQhBvV5/7bJ2gauHgr9eRMFfBX9dJVzqDs+LFOBpY6fzZMJF7wkhePDgAUEQvOTtTBLJtDhmEco8LNKDn/bMZGM6S/7Pmt5kGq+zws8igYuU68fzNVmW08r2tHKYtHmWh7q1tbWQfQVePwr+KvjrIlDw19uPKz3h+VUwTgzWWr788suXDnk7CwnMIpYR5smm8+Kd5jmdR9J9FbzpXv5l5HdafItKz+Nh551hNML4RmFaaz788MNXsLxAgYK/zoKCv6Y/X/DXfFzpzs9Z5MF5XleWZXzzzTcnO6OOr4aY1nCn/X8We6bJipM2je6Nk8e0yj2vwo/Hd17petpY+nlw2nPT7o/ytagNZyWYUfhxSXcRYp/2IzGtvoy/m5HEXK1WuXPnzgv5OwvOW/4XHUeBV0fBXwV/jaPgr9cXxyK4tNVeI7xKRhZ5dpr8N3p2dK/X67G3t7eQPDpJJqNKMRqzHb8+C7O2np/XKMYJZDL+eTLmZDyjpYxvI6ZJu+eJY4SzlsM8Yhl/N+N1C/L37TgOSilKpRLlchlrX95/pcDVR8FfBX+dFwV/vV14o7kbNZhFJdzzotlsMhgMXmqgcHpv+rJtm0znVdMa5edNS8GvgnH7x/NzVfM1IgqlFP1+n6dPn878USvw7qDgr5fTKfir4K+3Ba+98/MqDWTas7Ma/Oh/IQTPnj2bKw3Pi2vRe9P+zopxuxb5m/b8+KqCRdN8HQS+iEczzRM8DfPimszTReVvXvkD/O53v3vBGz7L31XBVbPnqqDgr9ko+Kvgr6uCRWx6Z3WtEXFYa3n06NFLE/MmC2VyV9TJuC4b48tGT8OsF7tohTwtn9Ok64vAopLuLM9pEvPKYRYuopFOPi+lfGFo4euvvz71kMUCBeah4K+Cv6ah4K+Lwxvr/Mx6gdMk3UUq8WS48e8HBwdnGkteVKa8KBnzohrpLJsXJZDxa6Px3vOOW59F6p1ly1WQiM9SD0blvLe3RxAEr8vEmfZchfJ7V1Hw14vxXAQK/rp4FPw1G++08mOtJU3TkzNxrkJlvCxMNtZRb370t2gcI5J9H3r+F4kReRhjODo6YjgcvmmTCrzFKPir4K/XifeRv8682mtcdpsl5c26dha57qzj19PGW621BEHA4eHhC1vCj+4bY1446G2apLio17ao7afFMaqAkw1+0iucJRmPh52Mc/R5Ur4dSdajZ0YS6LS0F5W1F8FkeS+aziLvf5G0p6W7aLzjdWbyehzHHB4esrGxcSabzoNF83GWeN5lFPz1Mgr+ehEFf70f/HXpys95iGMWFm2k4+EODg4Iw3Am6Y03sNPSniWFTl6bFva0v0mcp7zOM4Y8nofxsNPyMn79IjCPPOY9M0n0r+OHe55tSqmT+1prkiTh/v37V8JTP4t8X+BlFPxV8Ndp9k7acNozBX8tjsvkr3d22EsIgVKKR48eobWeGe51V8LLxDgBTBLJrMY/SRqvqwym2fgq4V4HZjU+Y8xJHVNKYYzhyZMnr9O0Au8YCv4q+OuiUfDXi7jUHZ5fRcqbvHZar29Swhv1sLe3t6fGOS6fzquY55HlJqXZ14GR3Dst3dPk2Gn2zrN/mlx6Xoy/i0kCm+YpjzyAyyCSaXFOK5fJOjH6rpQiTVOUUhwcHLyQj/PWifMMY5xFti8wGwV/vT4U/HUxtkyi4K/ZOFfn57SKBbPHsC8Ss+wYpaO15sGDB0gpT8bMp9k2r7Ke16Z55TDN3lkezLyynvQoRv9PrnSYRqqTmLdUdpbtr/I+JwltcoLieDlOlsV4Hl6FpM/y7Kw0R/YZY1BKnYR98uQJSZLged657VsEV0GafttQ8NfpNhX8NR8Ff10M3iR/vdPDXqPJgtOIaxGZ9LzjjWd9oRc1rjkvT+MeymWNoV4kropUvChGto7Gz9vt9ksrJt6WvBR48yj46+V7BX9dHt5H/jqX8rOolHva86+KeTKztZZWq0W/358q871qHs5q16J4VQ9zUqqcjPui0jlrHKeFW8TTPotsPwuX+b7H61UQBOzv77OysnLh6c2zYdb3WZ78+4iCv85u16Io+Gt23AV/nW7DrO+XwV+v9VT3yxrrnMQojVarRZqmL/TCJ2XI0/aDeBM/GosQ3DxJ2FqL1vol72gyvllS9bR0TrP1ojBuyzSye5Xx51lpnTcuIcQLUrHW+mTpcZZldDqdN9LZmPejWuD8KPhrMRT8VfDXq+B18ddr6fws2gCnhXuVFzvaH2O8Ec2SIs86XjwLr1qxX4WsrLUvjH2P2zLPpvOk+Sp2vgrhXDSBTNp1VlumeU2j93B0dHSy58h5ZfqrLO2/Lyj4a3EU/DUfBX9dHbxW5ed1Y39/fyHv6F3CRZHgVcZlEMd57ZgkDyG+3512cmfeN2H3eX4oC1wNFPx19vtvAwr+OpuNk7goG15L52eeLDkZ5rR7i0pi1loODw9RSp3sYTBOJNPk1PPiPGPRi3iR4xVyERuUUicrJcbzOavXft4x6Wlpz4rzNLyKl3xRUuhZbRiFHz9vaeQdaa1Pyn60THlU7+bVjbOkW+D1ouCvl1Hw18vhC/5a3M6rgAtf6j4Lky/oPERylsKz1tLr9V5I67yV5LSwk73j82IynUm7Jw83HLdvdG9kyyRpTDbwWWPTr2rzNMzqvS/aq5+8dpXk13GSB14o/6OjI5IkwXXdN+bpXQUP86qh4K+XwxX8NRsFf72b/PVOLXUfvURr88lbw+HwpQo62VhOa+yzxtjPG25RTI7zj/8/HmY8/fH/pxHR+N+0+AqcHdPKc3St1WoRRdFL4QoUmIaCvwr+et14n/nr3MNe0xrlvO9nwSxvZxE7xq+HYXgi1xljXvIsJsfS5+Vh0V7+IrYtGn5aOYxsH/9ujHlpUtosL2xaHs5i51l64pfVWMbzvqgMO69sp5HwIjL75L3xP2MM7XabwWBAvV6/8Lpy2fG86yj4q+Cv01Dw17vNXxei/Ew2soskkkXTHceoQY3IY3RtnDgmTx0+TzqXhVllOOn1ja6PME4spxHfKPw8G0aEe1WxqG2vw1McEfh42YdhSBiGU99JgauDgr8uFgV/LYaCv94sxBl7zYfA9uWZU6BAgSuGO9bajTdtxEWg4K8CBd5LTOWwM3V+ChQoUKBAgQIF3na8UxOeCxQoUKBAgQIFTkPR+SlQoECBAgUKvFcoOj8FChQoUKBAgfcKReenQIECBQoUKPBeoej8FChQoECBAgXeKxSdnwIFChQoUKDAe4Wi81OgQIECBQoUeK9QdH4KFChQoECBAu8Vis5PgQIFChQoUOC9wv8PgrGKoI+zfhwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_image(\n",
    "    ['./电商图像检索_数据集/test/'+x \n",
    "     for x in test_submit['label'].iloc[4].split()]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 310,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-08-07T16:32:17.663617Z",
     "iopub.status.busy": "2021-08-07T16:32:17.663063Z",
     "iopub.status.idle": "2021-08-07T16:32:17.844403Z",
     "shell.execute_reply": "2021-08-07T16:32:17.843919Z",
     "shell.execute_reply.started": "2021-08-07T16:32:17.663568Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_image(\n",
    "    ['./电商图像检索_数据集/test/'+x \n",
    "     for x in test_submit['label'].iloc[100].split()]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
